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

gallery/index.yaml

@@ -3295,7 +3295,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -3313,7 +3313,7 @@
   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:
@@ -3331,7 +3331,7 @@
   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:
@@ -6949,7 +6949,7 @@
       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
@@ -23049,3 +23049,32 @@
     - filename: YanoljaNEXT-Rosetta-27B-2511.i1-Q4_K_M.gguf
       sha256: 0a599099e93ad521045e17d82365a73c1738fff0603d6cb2c9557e96fbc907cb
       uri: huggingface://mradermacher/YanoljaNEXT-Rosetta-27B-2511-i1-GGUF/YanoljaNEXT-Rosetta-27B-2511.i1-Q4_K_M.gguf
+- !!merge <<: *qwen3vl
+  name: "qwen3vl_euclid_30b-i1"
+  urls:
+    - https://huggingface.co/mradermacher/Qwen3VL_Euclid_30B-i1-GGUF
+  description: |
+    The **Qwen3VL_Euclid_30B** is a large multimodal vision-language model based on the Qwen3 family, designed for advanced reasoning and understanding of both text and visual inputs. It is trained on the **Euclid30K** dataset, which includes diverse multimodal content, enabling strong performance in tasks such as image captioning, visual question answering, and complex reasoning over images and text.
+
+    This specific version is a **30-billion parameter** model with enhanced capabilities for handling high-resolution visual inputs and complex multimodal queries. The model supports **English and Chinese** and is built using the Hugging Face `transformers` library.
+
+    While the repository `mradermacher/Qwen3VL_Euclid_30B-i1-GGUF` contains **quantized GGUF versions** of the model (optimized for local inference with tools like `llama.cpp`), the original base model — which retains full precision and is suitable for research and high-fidelity applications — is hosted at **[LiamLian0727/Qwen3VL_Euclid_30B](https://huggingface.co/LiamLian0727/Qwen3VL_Euclid_30B)**.
+
+    > ✅ **For the original, full-precision model description and usage, refer to the base model repository.**
+    > 🔁 This quantized version is not the original model, but a downstream quantization by mradermacher for efficient local deployment.
+
+    **Key Features:**
+    - Multimodal: text + image input
+    - 30B parameters
+    - Trained on Euclid30K
+    - Supports English and Chinese
+    - Available in multiple quantizations for local inference (GGUF format)
+
+    **Ideal for:** Researchers, developers, and AI enthusiasts working with multimodal reasoning, especially those deploying models locally on consumer hardware.
+  overrides:
+    parameters:
+      model: Qwen3VL_Euclid_30B.i1-Q4_K_M.gguf
+  files:
+    - filename: Qwen3VL_Euclid_30B.i1-Q4_K_M.gguf
+      sha256: 565b9cf6137181dc784ab571801d315c4976b33ea4a3ee7de9d1caf2eceb019b
+      uri: huggingface://mradermacher/Qwen3VL_Euclid_30B-i1-GGUF/Qwen3VL_Euclid_30B.i1-Q4_K_M.gguf