ericksoa · Jul 15, 2026 · Jul 14, 2026 · Jul 14, 2026 · Jul 14, 2026 · Jul 14, 2026
diff --git a/ci/platform-matrix.json b/ci/platform-matrix.json
@@ -1,7 +1,7 @@
 {
   "$comment": "Single source of truth for NemoClaw launch claims and platform support. Covers platforms, inference providers, supported agents, messaging integrations, and deployment paths. Scripts read this to generate README and docs tables. QA/CI update platform/provider rows; the engineering owner reviews other rows. Docs are derived.",
   "version": "1.1",
-  "updated": "2026-07-12",
+  "updated": "2026-07-15",
 
   "project_status": {
     "stage": "alpha",
@@ -64,7 +64,7 @@
       "status": "deferred",
       "prd_priority": "P1",
       "ci_tested": false,
-      "notes": "The PRD marks this platform as P1. Workstation form-factor with NVIDIA GPUs and the same Docker + NVIDIA Container Toolkit + CDI requirements as DGX Spark. Onboard path not yet validated end-to-end on the hardware; vLLM defaults to `deepseek-ai/DeepSeek-V4-Flash` for this host class and will move out of `deferred` once the hardware run is signed off."
+      "notes": "The PRD marks this platform as P1. Workstation form-factor with NVIDIA GPUs and the same Docker + NVIDIA Container Toolkit + CDI requirements as DGX Spark. The installer detects DGX Station and offers express install with the pinned `nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4` recipe, including an approximately 352 GB model download, without follow-up provider, model, policy, or sandbox-name choices. Pass `--station-deepseek` to use `deepseek-ai/DeepSeek-V4-Flash` for a Station demo while retaining the one-confirmation express flow. Direct managed-vLLM onboarding still defaults to `deepseek-ai/DeepSeek-V4-Flash` when no model override is set. The full NemoClaw onboarding path, including the express recipe, has not been validated end-to-end on physical DGX Station hardware and remains `deferred` until that run is signed off."
     },
     {
       "name": "NVIDIA RTX (consumer and Pro workstation GPUs)",
@@ -147,7 +147,7 @@
       "name": "Local vLLM (managed install/start)",
       "status": "caveated",
       "endpoint_type": "Local OpenAI-compatible",
-      "notes": "Appears by default on DGX Spark and DGX Station. DGX Station remains deferred until its managed-vLLM onboarding path is validated end-to-end on physical hardware. Generic Linux NVIDIA GPU hosts require `NEMOCLAW_EXPERIMENTAL=1` or `NEMOCLAW_PROVIDER=install-vllm`. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (`onboard` asserts CDI presence). NemoClaw pins each host profile to an immutable NGC platform digest. DGX Spark and DGX Station use the `linux/arm64` digest published under `nvcr.io/nvidia/vllm:26.05.post1-py3`; generic Linux NVIDIA GPU hosts use the matching `linux/arm64` or `linux/amd64` digest published under `nvcr.io/nvidia/vllm:26.03.post1-py3`. Validated defaults are listed in `src/lib/inference/vllm-models.ts`: DGX Spark uses `nvidia/Qwen3.6-35B-A3B-NVFP4`, DGX Station uses `deepseek-ai/DeepSeek-V4-Flash`, and Linux NVIDIA GPU uses `nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8`. Image pulls require NGC registry login (`docker login nvcr.io`); onboard prompts for the NGC API key when authentication is missing."
+      "notes": "Appears by default on DGX Spark and DGX Station. DGX Station remains deferred until its managed-vLLM onboarding path is validated end-to-end on physical hardware. Generic Linux NVIDIA GPU hosts require `NEMOCLAW_EXPERIMENTAL=1` or `NEMOCLAW_PROVIDER=install-vllm`. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (`onboard` asserts CDI presence). NemoClaw pins runtime images to immutable digests. DGX Spark and DGX Station models without a model-specific runtime use the `linux/arm64` digest published under `nvcr.io/nvidia/vllm:26.05.post1-py3`; generic Linux NVIDIA GPU hosts use the matching `linux/arm64` or `linux/amd64` digest published under `nvcr.io/nvidia/vllm:26.03.post1-py3`. The DGX Station express installer selects `nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4` with a pinned Hugging Face revision and the multi-platform index digest published under `vllm/vllm-openai:v0.22.0`; that index resolves to the `linux/arm64` manifest on Station. Direct managed-vLLM profile defaults are listed in `src/lib/inference/vllm-models.ts`: DGX Spark uses `nvidia/Qwen3.6-35B-A3B-NVFP4`, DGX Station uses `deepseek-ai/DeepSeek-V4-Flash`, and Linux NVIDIA GPU uses `nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8`. Image pulls from `nvcr.io` require NGC registry login (`docker login nvcr.io`); onboard prompts for the NGC API key when authentication is missing."
     }
   ],
 

diff --git a/docs/get-started/quickstart.mdx b/docs/get-started/quickstart.mdx
@@ -120,6 +120,8 @@ Use these details when your first-run path needs more control.
     On macOS, start Docker Desktop or Colima first.
 
     DGX Spark, DGX Station, and Windows WSL offer an interactive express-install path that chooses a managed local inference option for the platform.
+    On DGX Station, accepting the express prompt selects the pinned `nemotron-3-ultra-550b-a55b` managed-vLLM recipe and completes onboarding without more provider, model, policy, or sandbox-name choices.
+    Pass `--station-deepseek` to use DeepSeek V4 Flash for a Station demo instead.
     Refer to [Platform Support](../reference/platform-support) and [Choose an Inference Provider](../inference/learn-and-choose/choose-inference-provider) for the current platform behavior.
 
     If `nemoclaw` is not found after installation and you use nvm or fnm, open a new terminal or reload your shell profile.
@@ -186,12 +188,19 @@ Use these details when your first-run path needs more control.
 
     On DGX Spark, DGX Station, and Windows WSL, interactive installation offers express install after you accept the third-party software notice.
     Express install switches onboarding to non-interactive mode, allows `sudo` password prompts for required host changes, and selects the managed local inference path for that platform.
-    DGX Spark uses managed vLLM with `qwen3.6-35b-a3b-nvfp4` by default, and DGX Station uses `deepseek-v4-flash` by default.
+    DGX Spark uses managed vLLM with `qwen3.6-35b-a3b-nvfp4` by default.
+    DGX Station express install explicitly selects `nemotron-3-ultra-550b-a55b` instead of the Station managed-vLLM profile default, `deepseek-v4-flash`, and discloses the approximately `352 GB` model download before confirmation.
+    To select DeepSeek V4 Flash while retaining the one-confirmation Station express flow, run `curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash -s -- --station-deepseek`.
     Unless `NEMOCLAW_POLICY_TIER` is set, express install applies policy in `suggested` mode with the `balanced` tier, including the base sandbox policy and supported package, model, web-search, and local-inference presets.
     Express install uses `my-assistant` as the sandbox name across all platforms unless `NEMOCLAW_SANDBOX_NAME` is set.
     Windows WSL selects the Windows-host Ollama setup path.
     Set `NEMOCLAW_NO_EXPRESS=1` to skip the express prompt, or set `NEMOCLAW_PROVIDER` before launching the installer to choose a provider yourself.
 
+    <Warning>
+    Express install automates the configuration but does not change DGX Station's Deferred support status.
+    Full NemoClaw onboarding with this recipe has not completed end-to-end validation on physical DGX Station hardware.
+    </Warning>
+
     The installer auto-launches `nemoclaw onboard` when it can find the new binary.
     If it cannot find the binary or blocking host preflight checks fail, it prints diagnostics and a `To finish setup, run:` block with the explicit `nemoclaw onboard` command.
 

diff --git a/docs/inference/choose-inference-provider.mdx b/docs/inference/choose-inference-provider.mdx
@@ -32,7 +32,7 @@ Use this status table to distinguish validated provider integrations from adapte
 | Local Ollama | Tested with limitations | Local Ollama API | Available when Ollama is installed or running on the host. Validated default models: `qwen3.6:35b` (high VRAM), `nemotron-3-nano:30b` (medium VRAM), `qwen3.5:9b` (low VRAM fallback). |
 | Local NVIDIA NIM | Experimental | Local OpenAI-compatible | Requires `NEMOCLAW_EXPERIMENTAL=1` and a NIM-capable NVIDIA GPU. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (`onboard` asserts CDI presence with `assertCdiNvidiaGpuSpecPresent`, `src/lib/onboard/fatal-runtime-preflight.ts`). NIM images pull from `nvcr.io` and require NGC registry login. NemoClaw gates this path behind the experimental flag because it does not auto-select a NIM image for the host today. You must explicitly pick from the validated image list. On Linux arm64 DGX Spark and DGX Station hosts, onboarding warns that some NIM images may not publish a `linux/arm64` manifest; the warning is advisory, and the selected image pull can still fail when the registry has no matching platform manifest. Managed vLLM has host-specific default models and is not gated on the same boxes. Validated images referenced in `src/lib/inference/config.ts` and `nemoclaw/src/index.ts`: `nvidia/nemotron-3-super-120b-a12b` (default cloud model), `nvidia/nemotron-3-nano-30b-a3b`, `nvidia/llama-3.3-nemotron-super-49b-v1.5`. |
 | Local vLLM (already running) | Tested with limitations | Local OpenAI-compatible | Appears in the onboarding menu when NemoClaw detects a server already on `localhost:8000`. No flag required. Model is whatever the existing server serves. |
-| Local vLLM (managed install/start) | Tested with limitations | Local OpenAI-compatible | Appears by default on DGX Spark and DGX Station. DGX Station remains deferred until its managed-vLLM onboarding path is validated end-to-end on physical hardware. Generic Linux NVIDIA GPU hosts require `NEMOCLAW_EXPERIMENTAL=1` or `NEMOCLAW_PROVIDER=install-vllm`. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (`onboard` asserts CDI presence). NemoClaw pins each host profile to an immutable NGC platform digest. DGX Spark and DGX Station use the `linux/arm64` digest published under `nvcr.io/nvidia/vllm:26.05.post1-py3`; generic Linux NVIDIA GPU hosts use the matching `linux/arm64` or `linux/amd64` digest published under `nvcr.io/nvidia/vllm:26.03.post1-py3`. Validated defaults are listed in `src/lib/inference/vllm-models.ts`: DGX Spark uses `nvidia/Qwen3.6-35B-A3B-NVFP4`, DGX Station uses `deepseek-ai/DeepSeek-V4-Flash`, and Linux NVIDIA GPU uses `nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8`. Image pulls require NGC registry login (`docker login nvcr.io`); onboard prompts for the NGC API key when authentication is missing. |
+| Local vLLM (managed install/start) | Tested with limitations | Local OpenAI-compatible | Appears by default on DGX Spark and DGX Station. DGX Station remains deferred until its managed-vLLM onboarding path is validated end-to-end on physical hardware. Generic Linux NVIDIA GPU hosts require `NEMOCLAW_EXPERIMENTAL=1` or `NEMOCLAW_PROVIDER=install-vllm`. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (`onboard` asserts CDI presence). NemoClaw pins runtime images to immutable digests. DGX Spark and DGX Station models without a model-specific runtime use the `linux/arm64` digest published under `nvcr.io/nvidia/vllm:26.05.post1-py3`; generic Linux NVIDIA GPU hosts use the matching `linux/arm64` or `linux/amd64` digest published under `nvcr.io/nvidia/vllm:26.03.post1-py3`. The DGX Station express installer selects `nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4` with a pinned Hugging Face revision and the multi-platform index digest published under `vllm/vllm-openai:v0.22.0`; that index resolves to the `linux/arm64` manifest on Station. Direct managed-vLLM profile defaults are listed in `src/lib/inference/vllm-models.ts`: DGX Spark uses `nvidia/Qwen3.6-35B-A3B-NVFP4`, DGX Station uses `deepseek-ai/DeepSeek-V4-Flash`, and Linux NVIDIA GPU uses `nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8`. Image pulls from `nvcr.io` require NGC registry login (`docker login nvcr.io`); onboard prompts for the NGC API key when authentication is missing. |
 {/* provider-status:end */}
 
 ## Hosted Providers