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Model details
Qwen3 14B
Qwen3-14B is a dense 14.8-billion-parameter language model from Alibaba's Qwen team that stands apart through its hybrid architecture, combining "thinking" and "non-thinking" modes within a single model. In thinking mode, it engages in deliberate, step-by-step reasoning suited for math, coding, and complex logical analysis; switching to non-thinking mode yields rapid, efficient responses for general-purpose dialogue. The architecture leverages grouped query attention with 40 query heads and 8 key-value heads across 40 layers, natively supporting a 32K-token context window. This dual-mode design means developers and researchers can deploy the same model for both deep analytical tasks and everyday conversations without managing separate systems. The model's agent capabilities allow precise integration with external tools, and its multilingual coverage spans over 100 languages, making it a flexible foundation for applications ranging from technical problem-solving to multilingual customer support.
Built through an extensive pretraining and post-training pipeline, Qwen3-14B was designed to surpass the performance of its predecessor QwQ in thinking scenarios and Qwen2.5 instruct models in non-thinking scenarios on benchmarks measuring mathematics, code generation, and commonsense reasoning. The model is open-weighted under the Apache 2.0 license, making it freely available for commercial use and research, with GGUF quantizations and Ollama support enabling efficient local deployment on consumer hardware. Its training emphasizes human preference alignment, yielding strong performance in creative writing, role-playing, and multi-turn conversations. The Qwen team positions Qwen3-14B as part of a broader family where even smaller variants like Qwen3-4B reportedly rival the performance of Qwen2.5-72B-Instruct, suggesting a substantial efficiency leap. Practical applications include embedding the model into AI assistants, automating coding workflows, supporting multilingual education platforms, and powering agents that reason and act across extended contexts.
Quick Info
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- Alibaba (China)
- Model key
- qwen3-14b
- Release date
- Apr 1, 2025
- Last updated
- Apr 1, 2025
- Knowledge cutoff
- 2025-04
- Input modalities
- Output modalities
- Capabilities
Cost
- Input token cost
- $0.144
- Output token cost
- $0.574
Limits
- Output tokens
- 8,192 tokens
- Context window
- 131,072 tokens
Transparent token rates
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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
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