Qwen3

# Qwen3

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    <img src="https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/logo_qwen3.png" width="400"/>
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          💜 <a href="https://chat.qwen.ai/"><b>Qwen Chat</b></a>&nbsp&nbsp | &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/organization/qwen">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://arxiv.org/abs/2505.09388">Paper</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen3/">Blog</a> &nbsp&nbsp ｜ &nbsp&nbsp📖 <a href="https://qwen.readthedocs.io/">Documentation</a>
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🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen3-Demo">Demo</a>&nbsp&nbsp | &nbsp&nbsp💬 <a href="https://github.com/QwenLM/Qwen/blob/main/assets/wechat.png">WeChat (微信)</a>&nbsp&nbsp | &nbsp&nbsp🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>&nbsp&nbsp
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Visit our Hugging Face or ModelScope organization (click links above), search checkpoints with names starting with `Qwen3-` or visit the [Qwen3 collection](https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f), and you will find all you need! Enjoy!

To learn more about Qwen3, feel free to read our documentation \[[EN](https://qwen.readthedocs.io/en/latest/)|[ZH](https://qwen.readthedocs.io/zh-cn/latest/)\]. 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 generat