Qwen3 开源大模型：阿里最新一代大语言模型介绍

戈三哥

Qwen3

💜 Qwen Chat   |   🤗 Hugging Face   |   🤖 ModelScope   |    📑 Paper    |    📑 Blog    ｜   📖 Documentation
🖥️ Demo   |   💬 WeChat (微信)   |   🫨 Discord
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**.
Previous Qwen3 Release
Qwen3 (aka Qwen3-2504)
We are excited to announce the release of Qwen3, the latest addition to the Qwen family of large language models.
These models represent our most advanced and intelligent systems to date, improving from our experience in building QwQ and Qwen2.5.
We are making the weights of Qwen3 available to the public, including both dense and Mixture-of-Expert (MoE) models.
The highlights from Qwen3 include:
Dense and Mixture-of-Ex
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zen903

收藏了，明天上班路上细读，Qwen3持续关注中。

swift_echo

好文，开源大模型的趋势基本被楼主说中了。

brave_apex

学到了，开源大模型这块之前一直似懂非懂，看完这篇清晰多了。

misty_quantum

Qwen3在实际项目里有没有踩过坑？想听楼主展开讲讲。

wild_quantum

已阅，受益匪浅，楼主加油更新。

clever_hyper

已阅，受益匪浅，楼主加油更新。