chore(model gallery): add vllm-omni models

gallery/index.yaml

@@ -129,6 +129,111 @@
     backend: neutts
     known_usecases:
       - tts
+- name: vllm-omni-z-image-turbo
+  license: apache-2.0
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  description: |
+    Z-Image-Turbo via vLLM-Omni - A distilled version of Z-Image optimized for speed with only 8 NFEs. Offers sub-second inference latency on enterprise-grade H800 GPUs and fits within 16GB VRAM. Excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence.
+  urls:
+    - https://huggingface.co/Tongyi-MAI/Z-Image-Turbo
+  tags:
+    - text-to-image
+    - image-generation
+    - vllm-omni
+    - z-image
+    - cpu
+    - gpu
+  overrides:
+    backend: vllm-omni
+    known_usecases:
+      - image_generation
+    parameters:
+      model: Tongyi-MAI/Z-Image-Turbo
+- name: vllm-omni-wan2.2-t2v
+  license: apache-2.0
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  description: |
+    Wan2.2-T2V-A14B via vLLM-Omni - Text-to-video generation model from Wan-AI. Generates high-quality videos from text prompts using a 14B parameter diffusion model.
+  urls:
+    - https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B-Diffusers
+  tags:
+    - text-to-video
+    - video-generation
+    - vllm-omni
+    - wan
+    - cpu
+    - gpu
+  overrides:
+    backend: vllm-omni
+    known_usecases:
+      - video_generation
+    parameters:
+      model: Wan-AI/Wan2.2-T2V-A14B-Diffusers
+- name: vllm-omni-wan2.2-i2v
+  license: apache-2.0
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  description: |
+    Wan2.2-I2V-A14B via vLLM-Omni - Image-to-video generation model from Wan-AI. Generates high-quality videos from images using a 14B parameter diffusion model.
+  urls:
+    - https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B-Diffusers
+  tags:
+    - image-to-video
+    - video-generation
+    - vllm-omni
+    - wan
+    - cpu
+    - gpu
+  overrides:
+    backend: vllm-omni
+    known_usecases:
+      - video_generation
+    parameters:
+      model: Wan-AI/Wan2.2-I2V-A14B-Diffusers
+- name: vllm-omni-qwen3-omni-30b
+  license: apache-2.0
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  description: |
+    Qwen3-Omni-30B-A3B-Instruct via vLLM-Omni - A large multimodal model (30B active, 3B activated per token) from Alibaba Qwen team. Supports text, image, audio, and video understanding with text and speech output. Features native multimodal understanding across all modalities.
+  urls:
+    - https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct
+  tags:
+    - llm
+    - multimodal
+    - vision
+    - audio
+    - video
+    - vllm-omni
+    - qwen3
+    - cpu
+    - gpu
+  overrides:
+    backend: vllm-omni
+    known_usecases:
+      - chat
+      - multimodal
+    parameters:
+      model: Qwen/Qwen3-Omni-30B-A3B-Instruct
+- name: vllm-omni-qwen3-tts-custom-voice
+  license: apache-2.0
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  description: |
+    Qwen3-TTS-12Hz-1.7B-CustomVoice via vLLM-Omni - Text-to-speech model from Alibaba Qwen team with custom voice cloning capabilities. Generates natural-sounding speech with voice personalization.
+  urls:
+    - https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
+  tags:
+    - tts
+    - text-to-speech
+    - voice-cloning
+    - vllm-omni
+    - qwen3
+    - cpu
+    - gpu
+  overrides:
+    backend: vllm-omni
+    known_usecases:
+      - tts
+    parameters:
+      model: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
 - name: "ace-step-turbo"
   license: mit
   tags:
@@ -161,7 +266,7 @@
       - "offload_to_cpu:false"
       - "offload_dit_to_cpu:false"
       - "init_lm:true"
       - "lm_model_path:acestep-5Hz-lm-0.6B" # or acestep-5Hz-lm-4B
       - "lm_backend:pt"
       - "temperature:0.85"
       - "top_p:0.9"
@@ -394,7 +499,7 @@
     known_usecases:
       - tts
     tts:
       voice: Aiden # Available speakers: Vivian, Serena, Uncle_Fu, Dylan, Eric, Ryan, Aiden, Ono_Anna, Sohee
     parameters:
       model: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
 - !!merge <<: *qwen-tts
@@ -406,7 +511,7 @@
     known_usecases:
       - tts
     tts:
       voice: Aiden # Available speakers: Vivian, Serena, Uncle_Fu, Dylan, Eric, Ryan, Aiden, Ono_Anna, Sohee
     parameters:
       model: Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice
 - &qwen-asr
@@ -4447,7 +4552,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -4465,7 +4570,7 @@
   description: |
     google/gemma-3-12b-it is an open-source, state-of-the-art, lightweight, multimodal model built from the same research and technology used to create the Gemini models. It is capable of handling text and image input and generating text output. It has a large context window of 128K tokens and supports over 140 languages. The 12B variant has been fine-tuned using the instruction-tuning approach. Gemma 3 models are suitable for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes them deployable in environments with limited resources such as laptops, desktops, or your own cloud infrastructure.
   overrides:
     #mmproj: gemma-3-12b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-12b-it-Q4_K_M.gguf
   files:
@@ -4483,7 +4588,7 @@
   description: |
     Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Gemma-3-4b-it is a 4 billion parameter model.
   overrides:
     #mmproj: gemma-3-4b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-4b-it-Q4_K_M.gguf
   files:
@@ -7701,7 +7806,7 @@
       sha256: 2756551de7d8ff7093c2c5eec1cd00f1868bc128433af53f5a8d434091d4eb5a
       uri: huggingface://Triangle104/Nano_Imp_1B-Q8_0-GGUF/nano_imp_1b-q8_0.gguf
 - &smollm
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## SmolLM
   name: "smollm-1.7b-instruct"
   icon: https://huggingface.co/datasets/HuggingFaceTB/images/resolve/main/banner_smol.png
   tags:
@@ -7745,7 +7850,7 @@
       sha256: decd2598bc2c8ed08c19adc3c8fdd461ee19ed5708679d1c54ef54a5a30d4f33
       uri: huggingface://HuggingFaceTB/SmolLM2-1.7B-Instruct-GGUF/smollm2-1.7b-instruct-q4_k_m.gguf
 - &llama31
   url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master" ## LLama3.1
   icon: https://avatars.githubusercontent.com/u/153379578
   name: "meta-llama-3.1-8b-instruct"
   license: llama3.1