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Welcome to Qwen!

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Welcome to Qwen!

.. figure:: https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/logo_qwen3.png :width: 60% :align: center :alt: Qwen3 :class: no-scaled-link

Qwen is the large language model and large multimodal model series of the Qwen Team, Alibaba Group. Both language models and multimodal models are pretrained on large-scale multilingual and multimodal data and post-trained on quality data for aligning to human preferences. Qwen is capable of natural language understanding, text generation, vision understanding, audio understanding, tool use, role play, playing as AI agent, etc.

Qwen3-2507

With input from the community and insights from further research, Instruct-only and Thinking-only models are coming back! The results are Qwen3-2507:

Qwen3-Instruct-2507 has the following features:

  • 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 long-context understanding, extensible to 1M.

Qwen3-Thinking-2507 has the following features:

  • 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-source 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, extensible to 1M.

Qwen3

Qwen3, aka Qwen3-2504, has the following features:

  • Dense and Mixture-of-Experts (MoE) models, available in 0.6B, 1.7B, 4B, 8B, 14B, 32B and 30B-A3B, 235B-A22B.
  • Seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose chat) within a single model, ensuring optimal performance across various scenarios.
  • Significantly enhancement in reasoning capabilities, surpassing previous QwQ (in thinking mode) and Qwen2.5 instruct models (in non-thinking mode) on mathematics, code generation, and commonsense logical reasoning.
  • Superior human preference alignment, excelling in creative writing, role-playing, multi-turn dialogues, and instruction following, to deliver a more natural, engaging, and immersive conversational experience.
  • Expertise in agent capabilities, enabling precise integration with external tools in both thinking and unthinking modes and achieving leading performance among open-source models in complex agent-based tasks.
  • Support of 100+ languages and dialects with strong capabilities for multilingual instruction following and translation.

For more information, please visit our:

  • Qwen Home Page <https://qwen.ai>__
  • Chat with Qwen (with Deep Research and Web Dev) <https://chat.qwen.ai>__
  • Blog <https://qwenlm.github.io/>__
  • GitHub <https://github.com/QwenLM>__
  • Hugging Face <https://huggingface.co/Qwen>__
  • ModelScope <https://modelscope.cn/organization/qwen>__
  • Qwen3 Collection <https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f>__

Join our community by joining our Discord <https://discord.gg/yPEP2vHTu4>__ and WeChat <https://github.com/QwenLM/Qwen/blob/main/assets/wechat.png>__ group. We are looking forward to seeing you there!

.. toctree:: :maxdepth: 1 :caption: Getting Started :hidden:

getting_started/quickstart getting_started/concepts getting_started/speed_benchmark getting_started/quantization_benchmark

.. toctree:: :maxdepth: 1 :caption: Inference :hidden:

inference/transformers

.. toctree:: :maxdepth: 1 :caption: Run Locally :hidden:

run_locally/llama.cpp run_locally/ollama run_locally/lmstudio run_locally/mlx-lm

.. toctree:: :maxdepth: 1 :caption: Deployment :hidden:

deployment/sglang deployment/vllm deployment/tgi deployment/dstack deployment/skypilot deployment/openllm

.. toctree:: :maxdepth: 1 :caption: Quantization :hidden:

quantization/awq quantization/gptq quantization/llama.cpp

.. toctree:: :maxdepth: 1 :caption: Training :hidden:

training/axolotl training/llama_factory training/ms_swift training/unsloth training/verl

.. toctree:: :maxdepth: 1 :caption: Framework :hidden:

framework/qwen_agent framework/function_call framework/LlamaIndex framework/Langchain