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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
| Date | Stars |
|---|---|
| 2026-07-31 | 27452 |
| 2026-08-01 | 27452 |
| 2026-08-06 | 27478 |
Today
+26 stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Qwen3
<p align="center">
<img src="https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/logo_qwen3.png" width="400"/>
<p>
<p align="center">
💜 <a href="https://chat.qwen.ai/"><b>Qwen Chat</b></a>   |   🤗 <a href="https://huggingface.co/Qwen">Hugging Face</a>   |   🤖 <a href="https://modelscope.cn/organization/qwen">ModelScope</a>   |    📑 <a href="https://arxiv.org/abs/2505.09388">Paper</a>    |    📑 <a href="https://qwenlm.github.io/blog/qwen3/">Blog</a>    ｜   📖 <a href="https://qwen.readthedocs.io/">Documentation</a>
<br>
🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen3-Demo">Demo</a>   |   💬 <a href="https://github.com/QwenLM/Qwen/blob/main/assets/wechat.png">WeChat (微信)</a>   |   🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>  
</p>
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 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**.
<details>
<summary><b>Previous Qwen3 Release</b></summary>
<h3>Qwen3 (aka Qwen3-2504)</h3>
<p>
We are excited to announce the release of Qwen3, the latest addition to the Qwen family of large laExcerpt of 24,697 characters
Read on GitHub
Ren Xuancheng
108
Junyang Lin · China
61
17
Binyuan Hui · Formerly @ Qwen · Singapore
16
Jianxin Ma · Tsinghua University
11
Yang An · Peking Univ. · China
10
Yang Fan · Tongyi Lab, Alibaba Group · China
6
Tiezhen WANG
6
HUANG Fei · @thu-coai · China
6
Zhanghao Wu · Sky Computing Lab, UC Berkeley · United States
5
Jianhong Tu
4
Xingjun.Wang · Tongyi Lab, Alibaba Group · China
3
Ethan Yang · Intel · China
3
Yunlin Mao · Tongyi Lab, Alibaba Group
3
Yang Jianxin · Sun Yat-Sen University · China
2
Ikko Eltociear Ashimine · Japan
2
2
1
Yaowei Zheng · Millennium Science School · China
1
Yineng Zhang · United States
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:94f5e768dc99c4ca, llm:Repository description: "Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud." (no topics provided).
matched fp:94f5e768dc99c4ca, llm:Repository description: "Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud." (no topics provided).
matched fp:94f5e768dc99c4ca, llm:Repository description: "Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud." (no topics provided).