Qwen3-32B represents the latest advancement in the Qwen series of large language models, offering a dense architecture expertly trained for groundbreaking performance. Qwen3 models are recognized for their seamless switching between thinking mode (complex logical reasoning, mathematics, and coding) and non-thinking mode (efficient, general-purpose dialogue) within a single framework, ensuring optimal performance across diverse scenarios.
Key highlights:
Outperforms previous QwQ and Qwen2.5 instruct models in mathematics, code generation, and commonsense logical reasoning.
Demonstrates superior alignment with human preferences, excelling at creative writing, role-play, multi-turn conversation, and instruction following for highly engaging and natural interactions.
Exhibits advanced agent capabilities, enabling accurate integration with external tools in both thinking and non-thinking modes for leading performance in complex agent-based tasks.
Provides strong multilingual support, covering over 100 languages and dialects with reliable instruction-following and translation capabilities.
Model overview:
| Feature | Description |
|---|---|
| Type | Causal Language Model |
| Training Stage | Pretraining & Post-training |
| Number of Parameters | 32.8B |
| Non-Embedding Parameters | 31.2B |
| Layers | 64 |
| Attention Heads (GQA) | Q: 64, KV: 8 |
| Context Length | 32,768 tokens natively, up to 131,072 tokens with YaRN |
Qwen3-32B sets a new benchmark for large language models in terms of reasoning, agent functionality, conversational quality, and multilingual support, making it an ideal solution for a variety of advanced AI applications.
