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Hybrid recurrent cache - #13979

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gabe-l-hart:HybridRecurrentCache
Jun 19, 2025
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ggerganov merged 39 commits into
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gabe-l-hart:HybridRecurrentCache

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@gabe-l-hart

@gabe-l-hart gabe-l-hart commented Jun 2, 2025 •

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This is a re-opened version of #13904 after #13746 was merged

Description

This PR introduces the llama_kv_cache_hybrid_recurrent cache implementation. It follows the pattern of llama_kv_cache_unified_iswa by holding two child cache instances and implementing the interface logic such that it manages both correctly for the appropriate layers.

Changes

The main change in this PR is the addition of llama_kv_cache_hybrid_recurrent in llama-kv-cache-hybrid-recurrent.*. In addition to this, the PR does the following:

  • Add the llama_model_is_hybrid_recurrent public API (akin to llama_model_is_recurrent)
  • Add LLM_KV_ATTENTION_LAYER_INDICES as an hparam to hold the indices of the layers that should use attention (versus recurrent)
    • This part is not well aligned with iswa, but that mechanism also isn't particularly extensible. It might be more appropriate to have a generic mechanism for indicating the type of caching to use for each layer, but that would start to approach the generic hybrid implementation that I originally attempted which ended up being too abstract (feat: Hybrid unified/recurrent cache #13276).
  • Abstracting utilities in llm_graph_context that need a specific type of cache to use getters (get_state_unified / get_state_recurrent) that will properly handle llama_kv_cache_hybrid_recurrent
  • Make n_embd_k_s / n_embd_v_s layer-dependent and use layer indices when calling them in the existing cache implementations
  • Add layer filtering to llama_kv_cache_recurrent
  • Updates the logic in llama_model::create_memory to use llm_arch_is_recurrent and llm_arch_is_hybrid_recurrent rather than relying on adding models to the switch statement which was redundant with the implementation of these functions

edits by @ggerganov below:

Notes so I don't forget

@gabe-l-hart gabe-l-hart mentioned this pull request Jun 2, 2025
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Comment thread src/llama-graph.cpp Outdated
Comment on lines 1063 to 1078

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These dynamic casts should not be necessary. Instead you need a new llm_graph_context::build_attn_inp_kv_hybrid_recurrent() method, similar to llm_graph_context::build_attn_inp_kv_unified_iswa().

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I'm working through this now and a couple of questions are coming up:

  1. Would it be best to combine build_inp_s_copy with build_attn_inp_kv for hybrid so that models call just one "build inputs" function, or keep them separate for simplicity?
  2. For the build_attn methods, each has a corresponding llm_graph_input_attn_* class. The build_inp_s_* methods don't have this pattern which would make this a bit harder to have code reuse. Are there plans to refactor that further @compilade?
  3. In the mamba2 branch, s_mask seems to be totally removed. I'd prefer not to do all of the boilerplate for duplicating build_inp_s_mask for the hybrid recurrent case if that's definitely going to be going away. Is there any reason that might stick around past the merge of mamba2?

@compilade compilade Jun 4, 2025 •

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Answering out of order, but it should still make sense:

2. For the build_attn methods, each has a corresponding llm_graph_input_attn_* class. The build_inp_s_* methods don't have this pattern

They do follow this pattern, see

class llm_graph_input_s_copy : public llm_graph_input_i {

(this is on the current master)

I think you might mean the build_attn_* methods also return instances of llm_graph_input_attn_*?
That seems to be directly related to llm_graph_context::build_attn() which has multiple implementations which differ by the type of the first argument (e.g. for llm_graph_input_attn_kv_unified, llm_graph_input_attn_no_cache, etc.)

Are there plans to refactor that further @compilade?

Not really, outside of removing s_mask (and related functions and classes) as part of #13834.

  1. Would it be best to combine build_inp_s_copy with build_attn_inp_kv for hybrid so that models call just one "build inputs" function, or keep them separate for simplicity?

Personally, I think it would be simpler to keep them separate, because they are fundamentally different (one is intended to be used by build_copy_mask_state (renamed to build_recurrent_state in #13834), while the other is used by build_attn), and they are pretty much independent, even in hybrid models (at least for Jamba, the recurrent and self-attention layers are mostly independent on that front).

I don't see how build_attn would ever need s_copy.

build_inp_s_copy and build_inp_attn_kv_* are called once at the beginning of the graph, while build_attn and build_recurrent_state are called once per layer (where applicable, and so usually different layers for both).

3. Is there any reason [s_mask] might stick around past the merge of mamba2?

No reason to keep it, s_mask will be removed. Its functionality is redundant with s_copy, and otherwise prevents minimizing unnecessary state copies. It was used to clear the states, but the same can be done through inp_s_copy and clearing by copying a zero-ed state (which is the rs_z'th state in the mamba2 branch (and #13834)).

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Thanks, that's super helpful! I was missing the distinction between build_attn_inp and build_attn which makes perfect sense.

Personally, I think it would be simpler to keep them separate

I agree on my personal gut feeling, so I'll go with this and see how it feels once complete.

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Ok, I think this feels a lot cleaner now. For build_inp_s_copy, I opted to add an optional parameter so that the caller can take ownership of casting the cache state rather than duplicating the function into build_inp_s_copy_hybrid. That felt a little cleaner w.r.t. code reuse, but I'm happy to do a separate method if that's preferred.

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It looks like there's one more place that will need changing in build_copy_mask_state (renamed to build_recurrent_state on mamba2). Similar to build_inp_s_copy, I think the cleanest way to do this for code reuse is to add an optional parameter that, if unset, will use the current logic of casting mstate.

Comment thread src/llama-kv-cache-hybrid-recurrent.cpp Outdated
Comment on lines 118 to 82

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Yes, but that will be fixed in #13834

(Noting here in case this gets merged first so that I don't forget to update the comment)

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Should I strip out this TODO at this point?

Comment thread src/llama-kv-cache-hybrid-recurrent.cpp Outdated
@gabe-l-hart
gabe-l-hart force-pushed the HybridRecurrentCache branch 7 times, most recently from ab918bb to 60ca3ba Compare June 9, 2025 16:06
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@ggerganov I've noticed that the Server tests are consistently failing on this branch, but I see them passing on other PRs (eg #14081). The failures seem to be around retried connections to /slots/0?action=restore (here). I've noticed a couple of things when trying to repro locally:

  1. For all of the server tests, despite the health check ping loop, I need to manually inject a sleep after server.start() to get any of the tests to pass on my M3 Max 64GB, otherwise the first endpoint call will almost always return an unexpected result (invalid json, or 5xx error). To me, this speaks to the server reporting /health success before it's logically "ready." This is probably correct in that the server is healthy enough to take requests, but the tests are treating this as a readiness check which would indicate that the server is fully initialized which seems incorrect (similar to liveness vs readiness in kubernetes). I wasn't able to find any open issues related to this, so I'd be curious if there's a discussion somewhere of readiness vs liveness?

  2. Once I do insert the manual sleep in test_slot_save_restore, the test passes locally for me. This speaks to some difference between my local system and the GH Action runners. I'm not familiar enough with the server code to know whether this would be caused by some kind of memory constraint, disk speed constraint, etc, but my guess would be something like slot1.bin not being fully written somehow. This wouldn't explain why it passes on other branches though. Any insight on the nature of these tests would be much appreciated as I try to debug!

@gabe-l-hart
gabe-l-hart requested a review from ngxson as a code owner June 9, 2025 17:36
@github-actions github-actions Bot added examples python python script changes server labels Jun 9, 2025
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I've tried adding retry logic for all requests in 39a93b3 to work around the race between /health, but I'm not sure if this is just going to mask an underling issue.

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The changes to the server tests should not be needed. Let's revert the commit for now and I'll investigate.

@gabe-l-hart
gabe-l-hart force-pushed the HybridRecurrentCache branch from 39a93b3 to 60ca3ba Compare June 9, 2025 20:13
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@ggerganov Thanks, it looks like those changes didn't fix the failures anyway, so definitely not the right fix. I've reset them out and can open an issue with details of what I see locally

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Issue for follow up on /health race condition with tests: #14092

@gabe-l-hart
gabe-l-hart force-pushed the HybridRecurrentCache branch 2 times, most recently from 7958d84 to 3669876 Compare June 10, 2025 21:22
@gabe-l-hart
gabe-l-hart marked this pull request as draft June 10, 2025 21:22
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I've rebased on #13834. Drafting for now until it's merged

@gabe-l-hart
gabe-l-hart force-pushed the HybridRecurrentCache branch from 3669876 to 8c59841 Compare June 10, 2025 22:22
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gabe-l-hart marked this pull request as ready for review June 10, 2025 22:22
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That was quick! Undrafting now that #13834 is merged

Comment thread src/llama-graph.h Outdated
It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
@gabe-l-hart

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Ok, renames/refactors done. 🤞 on Ci!

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Successfully rebased Granite 4 and verified that things are working as implemented here, including the refactor of the build_inp_mem_hybrid portions.

Comment thread src/llama-memory-recurrent.h Outdated
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
@ggerganov
ggerganov merged commit edc4a29 into ggml-org:master Jun 19, 2025
Comment thread src/llama-graph.h
Comment on lines +638 to +642
// TODO: move this implementation to llama_memory_recurrent.
// this is analogous to llama_kv_cache_unified::cpy_k / cpy_v
// when moving, avoid passing `ggml_cgraph` - only pass `ggml_context`. would likely need to split the
// implementation in 2 separate methods. the goal is to avoid calling `ggml_build_forward_expand` in
// `llama_memory_recurrent`

@compilade compilade Jun 19, 2025 •

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the goal is to avoid calling ggml_build_forward_expand

I'm not sure that would be convenient; build_rs when used with avoid_copies pretty much has to have a way to order the writes.

Splitting the function in two would require handling states_extra at call sites, while for now it's transparently handled within build_rs.

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I see. It's ok to pass the ggml_cgraph as argument in that case.

qnixsynapse pushed a commit to janhq/llama.cpp that referenced this pull request Jul 2, 2025
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
@gabe-l-hart
gabe-l-hart deleted the HybridRecurrentCache branch July 3, 2025 14:48
qnixsynapse pushed a commit to janhq/llama.cpp that referenced this pull request Jul 6, 2025
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
qnixsynapse pushed a commit to janhq/llama.cpp that referenced this pull request Jul 6, 2025
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
qnixsynapse pushed a commit to janhq/llama.cpp that referenced this pull request Jul 10, 2025
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
github-actions Bot pushed a commit to martin-steinegger/ProstT5-llama that referenced this pull request Jan 10, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org/llama.cpp#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Seunghhon pushed a commit to Seunghhon/llama.cpp that referenced this pull request Apr 26, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
my-other-github-account pushed a commit to my-other-github-account/llama.cpp that referenced this pull request May 15, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
AlexiAlp pushed a commit to minghaop/llama.cpp that referenced this pull request Jun 2, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
AlexiAlp pushed a commit to minghaop/llama.cpp that referenced this pull request Jun 2, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 5, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
The-Monk pushed a commit to The-Monk/llama.cpp that referenced this pull request Aug 5, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org/llama.cpp#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org/llama.cpp#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
zommiommy pushed a commit to zommiommy/llama.cpp that referenced this pull request Aug 18, 2026
* feat: Add llama_model_is_hybrid API call

Also, split llama_model_is_recurrent into llm_arch_is_recurrent in
llama-arch with llama_model_is_recurrent delegating to
llm_arch_is_recurrent. The same split is done for hybird. This is needed
because there are places where the llama_model has not yet been initialized
but we need to check if the model is recurrent (specifically for the
per-layer recurrent check array in hparams).

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add c++ side constants for attention layer indices hparam

Branch: GraniteFour

* feat: Add support for distinguishing recurrent vs non-recurrent layers in hparams

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Auto-fill hparams.recurrent_layer_arr based on whether the model is recurrent

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: rename *_is_hybrid -> *_is_hybrid_recurrent

The implementation of the hybrid cache intentionally does not specify the
types of the child caches, so there was a naming mismatch with these
predicate functions that used "hybrid" to imply "hybrid recurrent."

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add layer filter to recurrent cache

Branch: HybridCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer sizing everywhere in kv caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: First pass at llama_kv_cache_hybrid_recurrent

This follows the pattern in iswa where the two child caches are held
explicitly to support the case where a model requires a single attention
cache and a single recurrent cache where each layer uses exactly one of the
caches.

This is a rewrite of the more generic approach in the original hybrid cache
PR: ggml-org#13276

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Construct hybrid recurrent cache for hybrid recurrent models

This includes a refactor of the create_memory logic to avoid needing to use
the arch enum explicitly unless a model needs explicit cache instantiation
logic beyond the standard logic for recurrent, hybrid, unified, and iswa.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix wrong bool condition for split equal in hybrid cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix shift logic to defer to unified cache

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Support hybrid recurrent in llama-graph

NOTE: I intentionally did not add support for s_mask since it will be going
away soon

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix logic for initializing inputs and attn layers for hybrid caches

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update recurrent cache for changes to remove intermediate kv_cache interface

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix status for init_update sig for recurrent cache state

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add missing padding to n_ctx for hybrid cache construction

Branch: GraniteFour

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Update clear signature for data argument after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove errant virtual destructor leftover from previous impl attempt

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Use per-layer n_embd_k/v_s calls for mamba (1) layers

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_s from unified cache

No longer needed now that unified isn't also supporting recurrent

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

* refactor: Remove layer index from n_embd_k/v_s

Now that it's not used at all in the unified cache, we don't need to use
the layer index to zero it out for attention layers.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Remove n_embd_k/v_gqa from recurrent cache

This is no longer needed now that there are separate implementations

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Allow custom layer filters for hybrid recurrent

This should help support architectures like Falcon H1 where there is
overlap between layers that need attention and recurrent caches.

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove logits_all after rebase

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove llama_model_is_hybrid_Recurrent public API

ggml-org#13979 (comment)

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use llama_memory_state_ptr for child states in hybrid memory state

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Overhaul build_recurrent_state / build_inp_s_copy to match attention pattern

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2141701738

This is a big overhaul to bring consistency between how inputs and per-
layer components are created for attention layers and recurrent layers. The
main changes are:

- Rename class llm_graph_input_s_copy -> llm_graph_input_rs
- Add a corresponding llm_graph_input_rs_hybrid_recurrent
- Rename build_inp_s_copy -> build_rs_inp_recurrent
- Add a corresponding build_rs_inp_hybrid_recurrent
- Rename build_recurrent_state -> build_rs to match build_attn w/
llm_graph_input_rs android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a corresponding overload of build_rs w/
llm_graph_input_rs_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input
- Add a llm_graph_input_attn_kv_hybrid_recurrent analogous to
llm_graph_input_attn_kv_unified
- Add a build_attn override that takes
llm_graph_input_attn_kv_hybrid_recurrent android-build AUTHORS bamba-9b-2.2T.gguf bamba-9b-2.2T.q4_k_m.gguf broken.log build build-rel build-xcframework.sh build.android build.android.bak ci cmake CMakeLists.txt CMakePresets.json CODEOWNERS common common.o CONTRIBUTING.md convert_hf_to_gguf_update.py convert_hf_to_gguf.py convert_llama_ggml_to_gguf.py convert_lora_to_gguf.py debug.log docs examples flake.lock flake.nix ggml ggml-alloc.o ggml-backend.o ggml-metal.o ggml-model-BF16.gguf ggml-model-Q4_K_M.gguf ggml-quants.o ggml.o gguf-py grammar-parser.o grammars include LICENSE licenses llama.log llama.o llamacpp_trace.log main.log Makefile media models mypy.ini pocs poetry.lock prompts pyproject.toml pyrightconfig.json q4_k_m_boot.log q8_0_boot.log quant.log quant2.log README.md requirements requirements.txt sampling.o scripts SECURITY.md src test-grammar-output.tmp test-json-schema-input.tmp tests tools vendor working.log as the first input

This makes the two paradigms fully consistent. The main drawback is the
code duplication in the build_attn and build_rs implementations where the
only difference between implementations is how they cast the memory state.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix resize vs reserve and skip null tensors in size computation

https://github.com/ggml-org/llama.cpp/pull/13979/files#r2149469788

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: @younesbelkada

* fix: Fix initialization of child states

Since initially writing this PR, the logic in the child state types changed
such that using the "init full" signature and keeping the ubatches on the
parent struct no longer worked.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Use a common build_recurrent_state method that is cache-agnostic

This reduces the code duplication between the different build_rs impls and
also retains a similar signature to the previous build_recurrent_state
method while standardizing on the input-dispatched build_rs implementation.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* recurrent : rework graph inputs + add TODOs

ggml-ci

* refactor: Make status and child states const in hybrid and iswa

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: Rename llama_kv_cache_[recurrent|hybrid_recurrent] to remove kv cache

This removes the notion of "kv" from the interface names for these memory
types. There are still many references to kv in the implementation of the
recurrent memory which will need further adjustment.

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor!: Rename all k/v related values for recurrent/hybrid to r/s

Anywhere that "kv_<state|cell|size|etc>" is used, I've used the more
generic "mem_" prefix. The specifics of "k" (key) translate to "r"
(recurrent state) and "v" (value) translate to "s" (state-space embedding
states).

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refacor: _recurrent -> _recr for brevity

It just _happens_ to have the same number of letters as _attn!

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for ref

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* refactor: recurrent_layer() -> is_recurrent()

Branch: HybridRecurrentCache

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix spacing for size_s_bytes declaration

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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