Qwen3 is the latest generation of large language models in the Qwen series, offering a comprehensive suite of dense and mixture-of-experts models. Qwen3-14B is a 14.8 billion parameter causal language model that uniquely supports seamless switching between thinking mode for complex logical reasoning, mathematics, and coding, and non-thinking mode for efficient general-purpose dialogue within a single model. The model delivers significantly enhanced reasoning capabilities that surpass previous QwQ and Qwen2.5 instruct models on mathematics, code generation, and commonsense logical reasoning, while also excelling in human preference alignment for creative writing, role-playing, multi-turn dialogues, and instruction following. Qwen3-14B supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities, demonstrates expertise in agent capabilities for precise tool integration in both thinking and non-thinking modes, and natively supports context lengths of up to 32,768 tokens with extension to 131,072 tokens using YaRN scaling techniques.
Qwen3 is the latest generation of large language models in the Qwen series, offering a comprehensive suite of dense and mixture-of-experts models. Qwen3-14B is a 14.8 billion parameter causal language model that uniquely supports seamless switching between thinking mode for complex logical reasoning, mathematics, and coding, and non-thinking mode for efficient general-purpose dialogue within a single model. The model delivers significantly enhanced reasoning capabilities that surpass previous QwQ and Qwen2.5 instruct models on mathematics, code generation, and commonsense logical reasoning, while also excelling in human preference alignment for creative writing, role-playing, multi-turn dialogues, and instruction following. Qwen3-14B supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities, demonstrates expertise in agent capabilities for precise tool integration in both thinking and non-thinking modes, and natively supports context lengths of up to 32,768 tokens with extension to 131,072 tokens using YaRN scaling techniques.