This is a quantized version of the Alibaba Tongyi Deep Research 30B-A3B model. It uses MXFP4_MOE quantization technology and additionally adds imatrix quantization, aiming to optimize model performance and resource utilization efficiency, and is suitable for text generation tasks.

Natural Language ProcessingGguf

This project is the A3B quantized version of Alibaba's Tongyi In-depth Research 30B model. It aims to reduce the model deployment cost through quantization technology and make knowledge accessible to everyone. This model is optimized based on a large language model with a scale of 30B parameters, maintaining the strong capabilities of the original model while improving the inference efficiency.

Natural Language ProcessingGguf

Qwen2.5-VL-7B-Instruct is a multimodal vision-language model developed by the Tongyi Qianwen team at Alibaba. Based on a parameter scale of 7 billion, it is specifically optimized and trained for visual question-answering tasks. This model can understand and analyze image content and generate accurate natural language answers.

MultimodalSafetensorsEnglish

This is the GGUF quantized version of the Qwen/Qwen3-4B language model, a large language model with 4 billion parameters developed by Alibaba's Tongyi series. It is designed for consumer-grade hardware and supports powerful reasoning, intelligent agent workflows, and multilingual interaction.

Natural Language ProcessingGgufMultiple Languages

Qwen3-Next-80B-A3B-Instruct is a large-scale language model developed by the Tongyi Qianwen team of Alibaba Cloud. It has been optimized with 4-bit quantization using the MLX framework and specifically optimized for Apple chip devices to provide efficient inference capabilities.

Natural Language ProcessingTransformers

Qwen3-Next-80B-A3B-Instruct is the latest generation of large language model developed by the Tongyi Qianwen team at Alibaba. It adopts an innovative hybrid attention mechanism and a highly sparse mixture-of-experts architecture. While maintaining a total of 80B parameters, only 3B parameters are activated, achieving efficient context modeling and inference acceleration. It natively supports a context length of 262K and can be extended to 1M tokens.

Natural Language ProcessingTransformers

Qwen3-4B-Instruct is a large language model with 4 billion parameters developed by the Tongyi Qianwen team at Alibaba. It is optimized based on the Qwen3 architecture and specifically trained for dialogue and instruction-following tasks, with strong text generation and understanding capabilities.

Natural Language ProcessingTransformers

Qwen3-30B-A3B-Instruct-2507 is a large language model with 30 billion parameters launched by the Tongyi Qianwen team of Alibaba. It is specifically optimized for instruction following tasks. This model supports various natural language processing tasks such as text generation and dialogue interaction, and is open for developers to use through the LM Studio community model program.

Natural Language ProcessingGguf

Qwen3-Embedding-8B is an 8-billion parameter text embedding model developed by the Tongyi Qianwen team at Alibaba. It is optimized and implemented based on the MLX library and is specifically designed for sentence similarity calculation and text feature extraction tasks.

Natural Language ProcessingMlx

An English text re-ranking model based on the ModernBERT pre-training architecture, developed by Alibaba's Tongyi Lab, supporting long-text processing up to 8192 tokens.

Natural Language ProcessingTransformersEnglish

Qwen2.5-72B-Instruct is a large-scale language model developed by the Tongyi Qianwen team at Alibaba, with 72.7 billion parameters. This model has significant improvements in knowledge understanding, coding ability, mathematical reasoning, and multilingual support. It supports a context length of up to 128K tokens and can generate content of up to 8K tokens.

Natural Language ProcessingGgufMultiple Languages

An open-source video synthesis codebase developed by Alibaba's Tongyi Lab, integrating multiple advanced video generation models

MultimodalDiffusers