• mixture-of-experts — A model built from many specialist sub-networks where only a few activate per token, giving big-model capability at small-model running cost.
• context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
• open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
• benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.

Qwen3-Coder is an open-weight MoE model tuned specifically for agentic coding, tool-use, and browser-use, with 256K native (up to 1M) context and benchmark results rivaling Claude Sonnet 4 — making it one of the strongest open alternatives for self-hosted or cost-controlled coding agents.

• articleChinese CLIP: Contrastive Vision-Language Pretraining in Chinese
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• articleQwen1.5-MoE: Matching 7B Model Performance with 1/3 Activated Parameters
• articleGeneralizing an LLM from 8k to 1M Context using Qwen-Agent

• articleQwen2.5-Coder: Code More, Learn More!Qwen Team
• articleQwen2.5-Coder Series: Powerful, Diverse, Practical.Qwen Team
• articleQwen3: Think Deeper, Act FasterQwen Team

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