README

Qwen3


    



          💜 Qwen Chat&nbsp&nbsp | &nbsp&nbsp🤗 Hugging Face&nbsp&nbsp | &nbsp&nbsp🤖 ModelScope&nbsp&nbsp | &nbsp&nbsp 📑 Paper &nbsp&nbsp | &nbsp&nbsp 📑 Blog &nbsp&nbsp ｜ &nbsp&nbsp📖 Documentation

🖥️ Demo&nbsp&nbsp | &nbsp&nbsp💬 WeChat (微信)&nbsp&nbsp | &nbsp&nbsp🫨 Discord&nbsp&nbsp



Visit our Hugging Face or ModelScope organization (click links above), search checkpoints with names starting with Qwen3- or visit the Qwen3 collection, and you will find all you need! Enjoy!

To learn more about Qwen3, feel free to read our documentation \[EN|ZH\]. Our documentation consists of the following sections:

- Quickstart: the basic usages and demonstrations;
- Inference: the guidance for the inference with Transformers, including batch inference, streaming, etc.;
- Run Locally: the instructions for running LLM locally on CPU and GPU, with frameworks like llama.cpp, Ollama, and LM Studio;
- Deployment: the demonstration of how to deploy Qwen for large-scale inference with frameworks like SGLang, vLLM, TGI, etc.;
- Quantization: the practice of quantizing LLMs with GPTQ, AWQ, as well as the guidance for how to make high-quality quantized GGUF files;
- Training: the instructions for post-training, including SFT and RLHF (TODO) with frameworks like Axolotl, LLaMA-Factory, etc.
- Framework: the usage of Qwen with frameworks for application, e.g., RAG, Agent, etc.

 Introduction

 Qwen3-2507

Over the past three months, we continued to explore the potential of the Qwen3 families and we are excited to introduce the updated Qwen3-2507 in two variants, Qwen3-Instruct-2507 and Qwen3-Thinking-2507, and three sizes, 235B-A22B, 30B-A3B, and 4B.

Qwen3-Instruct-2507 is the updated version of the previous Qwen3 non-thinking mode, featuring the following key enhancements:  

- Significant improvements in general capabilities, including instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage.  
- Substantial gains in long-tail knowledge coverage across multiple languages.  
- Markedly better alignment with user preferences in subjective and open-ended tasks, enabling more helpful responses and higher-quality text generation.  
- Enhanced capabilities in 256K-token long-context understanding, extendable up to 1 million tokens.

Qwen3-Thinking-2507 is the continuation of Qwen3 thinking model, with improved quality and depth of reasoning, featuring the following key enhancements:
- Significantly improved performance on reasoning tasks, including logical reasoning, mathematics, science, coding, and academic benchmarks that typically require human expertise — achieving state-of-the-art results among open-weight thinking models.
- Markedly better general capabilities, such as instruction following, tool usage, text generation, and alignment with human preferences.
- Enhanced 256K long-context understanding capabilities, extendable up to 1 million tokens.



    Previous Qwen3 Release
    Qwen3 (aka Qwen3-2504)