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Qwen3.8-Max is advertised as a 2.4 trillion-parameter model; Alibaba posted on…

2026-08-03 · 02:15 UTC ·@Alibaba_Qwen ·1 min read

Brief

Qwen3.8-Max, a 2.4‑trillion-parameter model, will have its open weights released the week after Alibaba’s 2026-08-03 announcement; Qwen3.8-27B will also be open-sourced. Alibaba claims 10+ days of autonomous, self-evolving coding (GitHub trace provided), production-quality outputs across hundreds of professions, long-horizon planning (500+ chip-design turns, 365‑day e‑commerce strategy) and native multimodal vision, with published token pricing and API/studio links.

Why it matters

Qwen3.8-Max is advertised as a 2.4 trillion-parameter model; Alibaba posted on 2026-08-03 that Qwen3.8-Max open weights will be released “next week” and that Qwen3.8-27B will also be released as open-weights.

Key details

  • Alibaba claims autonomous coding capability: 10+ days of self-evolving development from an empty folder to production with a GitHub project trace (github.com/qwen-code-dev-bot…), production-quality deliverables across “hundreds of professions,” long-horizon planning (500+ chip-design optimization turns; 365 days of e‑commerce strategy), and native multimodal vision as a continuous feedback loop.
  • Published pricing: input $2.0 per 1M tokens, output $6.0 per 1M tokens, implicit caching $0.25 per 1M tokens; blog, Qwen Studio, and API links were provided (qwen.ai/blog?id=qwen3.8, chat.qwen.ai, qwencloud.com).
Source evidence

📢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：github.com/qwen-code-dev-bot…
  • 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! 🚀

📖 Blog: qwen.ai/blog?id=qwen3.8
✅ Qwen Studio: chat.qwen.ai/?models=qwen3.8…
⚡ API: qwencloud.com/models/qwen3.8…