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Qwen3.8-Max ran an autonomous coding project for 16 days, turning an empty folder…

2026-08-04 · 03:56 UTC ·@minchoi ·1 min read

Brief

Qwen3.8-Max is a 2.4T-parameter model Alibaba says ran a 16-day autonomous coding run that converted an empty folder into a production app (full GitHub trace available). It claims long-horizon planning (500+ chip-design turns, 365-day e-commerce strategies), native multimodal feedback, and open weights release next week alongside Qwen3.8-27B; pricing published.

Why it matters

Qwen3.8-Max ran an autonomous coding project for 16 days, turning an empty folder into a production app; the author posted a full project trace on GitHub (github.com/qwen-code-dev-bot…).

Key details

  • Model specs and claims: 2.4T parameters; advertised 'long-horizon mastery' including 500+ turns of chip-design optimization and 365 days of e-commerce strategy; native multimodal intelligence with vision as continuous feedback.
  • Release and pricing: open weights for Qwen3.8-Max (and Qwen3.8-27B) announced for next week; pricing listed as Input $2.0 / M tokens, Output $6.0 / M tokens, Implicit Caching $0.25 / M tokens, with blog/API/Studio links provided.
Source evidence

Qwen3.8-Max ran an autonomous coding project for 16 days.

Empty folder → production app.
No hand-holding.
Full GitHub trace.

Open weights next week.

Video

Qwen (@Alibaba_Qwen)

📢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…

— https://nitter.net/Alibaba_Qwen/status/2084100707423289643#m