📢 Meet Qwen3.8-Max, our most capable model to date. A new bar for coding and work at 2.4T parameters: 🔵 Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub：qwen-code-dev-bot/oh-my-cli. 🔵 Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. Start building with Qwen3.8-Max! 🚀

📢 Meet Qwen3.8-Max, our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: 🔵 Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub：qwen-code-dev-bot/oh-my-cli. ⚪ Real work, real results: Production-quality deliverables across hundreds of professions. 🔵 Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. ️ ⚪ Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max! 🚀

The number that decides whether anyone can actually use the 1M window is the cache, not the $2 input. Full context is $2 a call before you get a single token back, and $0.25 cached is the only reason a long agent loop pencils out. So the spec I want published is the implicit cache TTL and what invalidates it. Implicit is lovely until you're forecasting a month of spend and can't explain why the hit rate moved.

Qwen3.8-Max

A New Bar for Coding and Cowork

A New Bar for Coding and Cowork