This is the quantized version of Qwen3-VL-32B-Thinking-heretic, using a new ablation method for quantization. Compared with traditional methods, it causes less damage to the base model. It offers multiple quantization precision versions and is suitable for running on devices with 24GB of VRAM, supporting image-to-text tasks.

MultimodalTransformersEnglish

TomoroAI/tomoro-colqwen3-embed-4b is an advanced ColPali-style multimodal embedding model that can map text queries, visual documents (such as images, PDFs) or short videos into aligned multi-vector embeddings. This model combines the advantages of Qwen3-VL-4B-Instruct and Qwen3-Embedding-4B, performs excellently in the ViDoRe benchmark test, and significantly reduces the embedding space occupation.

MultimodalTransformersOther

Qwen3 VL 4B Thinking is a multimodal model that supports image-to-text and text-to-text conversion. It has a parameter scale of 4B and can meet various image-text interaction needs.

MultimodalGguf

Qwen3-VL-4B-Instruct is a 4-billion-parameter visual language model launched by Alibaba. It is developed based on the Qwen3 architecture and supports multimodal understanding and dialogue tasks. This model has powerful image understanding and text generation capabilities, and can handle complex visual language interaction scenarios.

MultimodalTransformers

This is an uncensored version based on Qwen/Qwen3-VL-32B-Instruct, created using Heretic v1.0.1. This model is a powerful vision-language model with advanced visual understanding, text understanding, and multimodal reasoning capabilities, supporting various tasks such as image analysis, video understanding, and interface operation.

MultimodalTransformers

This is a mixed quantization version based on the Qwen3 VL 8B model, which uses MXFP4 quantization technology and mixed weights on the dense model. While maintaining accuracy close to Q8, this model achieves a smaller file size and higher inference speed, making it an excellent solution for balancing efficiency and accuracy.

MultimodalSafetensorsOther

This is an experimental mixed quantization version based on the Qwen3 VL 8B model. It uses the MXFP4_MOE technology combined with high-precision weights to achieve a smaller file size and higher inference speed while maintaining accuracy close to Q8. This model explores mixed quantization methods and achieves a good balance between accuracy loss and performance.

MultimodalSafetensorsOther

A large language model with 12B parameters fine-tuned based on Qwen 3, capable of handling 256k ultra-long contexts. It is specifically optimized for long text generation tasks. This model combines the foundation of the VLTO 8B model, Brainstorm 20x tuning, and NEO Imatrix dataset quantization technology, enabling it to generate high-quality long text content.

Natural Language ProcessingGgufMultiple Languages

This is an enhanced multimodal vision-language model based on the Qwen3-VL-8B-Thinking model. It is extended to 12B parameters through Brainstorm 20x technology and uses NEO Imatrix-enhanced GGUF quantization. The model has powerful image understanding, text generation, and multimodal reasoning capabilities, with significant improvements in visual perception, text quality, and creative scenarios.

MultimodalGgufMultiple Languages

nutrient-gram-qwen-3-vl-2b is a fine-tuned version based on Qwen/Qwen3-VL-2B-Instruct, trained using TRL for supervised fine-tuning, mainly used for text generation tasks. This model is optimized for specific tasks while maintaining its original multimodal capabilities.

Natural Language ProcessingTransformers

This is a GGUF format version converted from the Qwen3-VL-30B-A3B-Instruct model, specifically optimized for llama.cpp. This model is a multimodal visual language model with 30 billion parameters, supporting image understanding and text generation tasks.

MultimodalGguf

This is a quantized version model based on Qwen3-VL-30B, specifically designed for image-text to text conversion tasks. The model optimizes the original model through quantization technology, providing a more efficient inference solution.

MultimodalGguf

Qwen3-VL is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalGguf

This is a quantized version of the Huihui Qwen3-VL-8B thinking ablated model. Based on the Qwen3-VL-8B architecture, it is specifically optimized and quantized for image-text conversion tasks and can be efficiently run through the llama.cpp tool.

MultimodalGguf

The quantized version of the Huihui Qwen3-VL-8B instruction ablation model, specifically designed for image-text to text conversion tasks. This model is based on the Qwen3-VL-8B architecture, optimized through instruction ablation and quantized, which can reduce the computational resource requirements while maintaining performance.

MultimodalGguf

The quantized version of the Huihui Qwen3-VL-4B thinking elimination model, optimized based on the Qwen3-VL-4B model, is specifically designed to eliminate the thinking chain reasoning process and can be used with the latest llama.cpp to provide efficient image-text to text processing capabilities.

MultimodalGguf

Qwen3-VL-32B-Thinking is the most powerful vision-language model in the Qwen series, with excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context processing, spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL-8B-Thinking is the most powerful vision-language model in the Tongyi Qianwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalGguf

Qwen3-VL is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in - depth visual perception and reasoning capabilities, long - context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision - language model in the Tongyi series, with comprehensive upgrades in text understanding and generation, visual perception and reasoning, context length, spatial and video dynamic understanding, and agent interaction capabilities. This model offers both dense architecture and mixture - of - experts architecture, supporting flexible deployment from edge devices to the cloud.

MultimodalTransformers