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@GenAI_is_real says the 27B open-weight release is the most exciting, arguing…

2026-08-03 · 04:50 UTC ·@GenAI_is_real ·1 min read

Brief

Qwen's recent model wave centers on new open-weight releases: @GenAIisreal highlights the 27B (~30B) class as the sweet spot for local deployment and ASR prototyping without API costs. Alibaba Qwen announced Qwen3.8-Max (2.4T parameters) and an open-weight Qwen3.8-27B next week, touting autonomous coding and multimodal, long-horizon capabilities.

Why it matters

@GenAI_is_real says the 27B open-weight release is the most exciting, arguing models in the ~30B range are the "sweet spot" for local deployment and are essential for building local ASR workflows to avoid API round-trips and per-token costs.

Key details

  • Alibaba Qwen announced Qwen3.8-Max (2.4T parameters) and said open weights for Qwen3.8-Max and Qwen3.8-27B will be released next week.
  • Qwen advertises Qwen3.8-Max capabilities — 10+ days of autonomous coding to production, production-quality deliverables across hundreds of professions, 500+ turns of chip-design optimization, 365 days of e-commerce strategy, and native multimodal continuous feedback — and listed pricing: Input $2.0/M tokens, Output $6.0/M tokens, Implicit Caching $0.25/M tokens.
Source evidence

Congrats to the Qwen team! The recent wave of model releases across the ecosystem has been genuinely impressive, but what stands out to me here is the continued commitment to open weights at the sizes that actually matter for practitioners.

The 27B open-weight release is the one I'm most excited about. A model in the ~30B range is the sweet spot for local deployment - large enough to be genuinely capable, small enough to run on accessible hardware. For my own work, this size class has become essential to building local ASR workflows where I need reliable language modeling without depending on API round-trips or worrying about per-token costs. The difference between "I can prototype this locally" and "I need to provision cloud inference" often comes down to exactly this size band, and Qwen consistently delivers strong models right in it.

Qwen has been one of the most reliable contributors to the open ecosystem - strong models, honest benchmarks, and weights that actually ship. Looking forward to getting 3.8-27B running and putting it to work. Thank you for continuing to build in the open.

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