Qwen3 Highlights

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features:

• Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios.
• Significantly enhancement in its 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.

Model Overview

Qwen3-8B has the following features:

• Type: Causal Language Models
• Training Stage: Pretraining & Post-training
• Number of Parameters: 8.2B
• Number of Paramaters (Non-Embedding): 6.95B
• Number of Layers: 36
• Number of Attention Heads (GQA): 32 for Q and 8 for KV
• Context Length: 32,768 natively and 131,072 tokens with YaRN.

For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our blog, GitHub, and Documentation.

Quickstart

• vLLM:

For local use, applications such as Ollama, LMStudio, MLX-LM, llama.cpp, and KTransformers have also supported Qwen3.

Switching Between Thinking and Non-Thinking Mode

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We provide a hard switch to strictly disable the model's thinking behavior, aligning its functionality with the previous Qwen2.5-Instruct models. This mode is particularly useful in scenarios where disabling thinking is essential for enhancing efficiency.

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In this mode, the model will not generate any think content and will not include a INLINECODE220A0303F2 block.

> [!NOTE]
> For non-thinking mode, we suggest using INLINECODE23410C0AC6, INLINECODE24D5E03085, INLINECODE25C1B2F8D0, and INLINECODE265B959F22. For more detailed guidance, please refer to the Best Practices section.

Advanced Usage: Switching Between Thinking and Non-Thinking Modes via User Input

Here is an example of a multi-turn conversation:

Agentic Use

Qwen3 excels in tool calling capabilities. We recommend using Qwen-Agent to make the best use of agentic ability of Qwen3. Qwen-Agent encapsulates tool-calling templates and tool-calling parsers internally, greatly reducing coding complexity.

To define the available tools, you can use the MCP configuration file, use the integrated tool of Qwen-Agent, or integrate other tools by yourself.
INLINECODE40171819F8INLINECODE410FEEF427transformersINLINECODE42F75C716Fllama.cppINLINECODE4301E0C158vllmINLINECODE445B08A248sglangINLINECODE4589F926E8config.jsonINLINECODE46AF35A355ropescalingINLINECODE47547CEAEDINLINECODE496227E80AINLINECODE503BA2515Allama.cppINLINECODE519F66D2E8vllmINLINECODE52C3BCB099INLINECODE54E048760DINLINECODE55FAFCACFDsglangINLINECODE5641627319INLINECODE5852567E3AINLINECODE5937FB02F6llama-serverINLINECODE60180847F9llama.cppINLINECODE61EB7EE44AINLINECODE632973681DINLINECODE64DC10C8DAINLINECODE660A8FC603 for 'ropetype'='yarn': {'originalmaxpositionembeddings'}
> INLINECODE69EA0C967CropescalingINLINECODE7066FBA89EfactorINLINECODE710525BABFfactorINLINECODE72A9385AA8maxpositionembeddingsINLINECODE73519F84A8config.jsonINLINECODE74DB05D17Fenablethinking=TrueINLINECODE75923209AETemperature=0.6INLINECODE7615D8703BTopP=0.95INLINECODE7717ACB621TopK=20INLINECODE784C5026F5MinP=0INLINECODE7943F8D96Aenablethinking=FalseINLINECODE80CA14A583Temperature=0.7INLINECODE8171A144CBTopP=0.8INLINECODE821EE757C2TopK=20INLINECODE83DF81F09EMinP=0INLINECODE84BC71E7F6presencepenaltyINLINECODE854FBF09BEanswerINLINECODE86849894CA"answer": "C"`."

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