chore(model gallery): 🤖 add 1 new models via gallery agent

gallery/index.yaml

@@ -3309,7 +3309,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -3327,7 +3327,7 @@
   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:
@@ -3345,7 +3345,7 @@
   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:
@@ -6963,7 +6963,7 @@
       sha256: 2756551de7d8ff7093c2c5eec1cd00f1868bc128433af53f5a8d434091d4eb5a
       uri: huggingface://Triangle104/Nano_Imp_1B-Q8_0-GGUF/nano_imp_1b-q8_0.gguf
 - &qwen25
   name: "qwen2.5-14b-instruct" ## Qwen2.5
   icon: https://avatars.githubusercontent.com/u/141221163
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
   license: apache-2.0
@@ -23363,3 +23363,29 @@
     - filename: Qwen3-Grand-Horror-Light-1.7B.Q4_K_M.gguf
       sha256: cbbb0c5f6874130a8ae253377fdc7ad25fa2c1e9bb45f1aaad88db853ef985dc
       uri: huggingface://mradermacher/Qwen3-Grand-Horror-Light-1.7B-GGUF/Qwen3-Grand-Horror-Light-1.7B.Q4_K_M.gguf
+- !!merge <<: *qwen3vl
+  name: "qwen.qwen3-vl-235b-a22b-thinking"
+  urls:
+    - https://huggingface.co/DevQuasar/Qwen.Qwen3-VL-235B-A22B-Thinking-GGUF
+  description: |
+    The **Qwen3-VL-235B-A22B-Thinking** is a large multimodal language model developed by Alibaba Cloud as part of the Qwen series. It is a 235-billion-parameter variant designed for advanced reasoning and multimodal understanding, capable of processing both text and images. This model excels in complex tasks such as visual question answering, image captioning, reasoning over visual content, and long-form text generation with deep contextual awareness.
+
+    Key features:
+    - **Multimodal capability**: Integrates vision and language models to interpret and reason over images and text.
+    - **Advanced reasoning**: Built with a “Thinking” architecture that enables step-by-step reasoning, improving performance on logic, math, and complex problem-solving tasks.
+    - **Large-scale training**: Trained on vast amounts of diverse data, enabling strong generalization and robustness across domains.
+    - **High accuracy and coherence**: Delivers fluent, factually consistent, and contextually relevant outputs.
+
+    This model is ideal for research, AI assistants, content creation, and any application requiring deep understanding of visual and textual information.
+
+    > 🔗 Base model: [Qwen/Qwen3-VL-235B-A22B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Thinking)
+    > 📦 Repository: [DevQuasar/Qwen.Qwen3-VL-235B-A22B-Thinking-GGUF](https://huggingface.co/DevQuasar/Qwen.Qwen3-VL-235B-A22B-Thinking-GGUF) — a quantized GGUF version for efficient local inference.
+
+    Note: The version on Hugging Face (DevQuasar) is a quantized GGUF format for local deployment; the original, full-precision model is maintained by Alibaba's Qwen team.
+  overrides:
+    parameters:
+      model: Qwen.Qwen3-VL-235B-A22B-Thinking.Q4_K_M-00001-of-00011.gguf
+  files:
+    - filename: Qwen.Qwen3-VL-235B-A22B-Thinking.Q4_K_M-00001-of-00011.gguf
+      sha256: 246cda7f9e1f173fc57310e9bdbef86883f9989f69391a76fd41ec1b48d39f97
+      uri: huggingface://DevQuasar/Qwen.Qwen3-VL-235B-A22B-Thinking-GGUF/Qwen.Qwen3-VL-235B-A22B-Thinking.Q4_K_M-00001-of-00011.gguf