Qwen3.8-27B

Qwen3.8-27B

Alibaba
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About

Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning, scaling test‑case generation for diverse coding challenges, and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and environment variables.

About

Qwen3.8-27B is a compact open-weights model in Alibaba’s Qwen3.8 family, aimed at developers and researchers who want strong local AI performance without using the full Max-scale model. Reports from Alibaba’s Qwen3.8 launch state that Qwen3.8-27B was planned for open-weight release alongside Qwen3.8-Max, expanding access for builders working on AI applications. The model is positioned for coding, research, professional workflows, and local deployment scenarios where a 27B model can be more practical than frontier-scale systems. Qwen3.8’s broader launch emphasizes software development, document processing, data analysis, and professional “cowork” use cases. Qwen3.8-27B is especially relevant for teams that need a capable open model for experimentation, coding agents, assistant workflows, and self-hosted inference. Built for practical deployment, Qwen3.8-27B gives developers a smaller Qwen3.8 option for building AI tools, testing agents, and running advanced language model workflows.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI researchers and software engineers wanting a solution offering an agentic coding model with large‑context support and turnkey CLI tools for real‑world, automated code generation

Audience

Software developers, AI researchers, coding agent builders, local LLM users, startup teams, enterprise AI teams, infrastructure teams, data teams, and organizations that need an open-weights 27B model for coding assistance, agent testing, self-hosted inference, document processing, data analysis, workflow automation, model benchmarking, private deployment, and Qwen-family experimentation

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Pros & Cons from Real Users

Pros

  • A 27B model is big enough to be useful for serious coding, reasoning, writing, and local-agent workflows, but still small enough that developers can realistically experiment with quantized versions on enthusiast hardware. That is the sweet spot for a lot of builders. Not everyone wants a massive cloud-only model, and not every workflow needs a 2T+ parameter system. A strong 27B model can be great for private coding help, local RAG, repo exploration, prompt testing, and lightweight agents. I also like the open-weight/local angle. Community reports around Qwen3.8-27B are already focused on GGUFs, MLX builds, VRAM needs, and local performance, which is exactly the kind of ecosystem momentum that makes a model useful beyond a demo.

Cons

  • The main downside is clarity. I would want a stable official model card, confirmed architecture details, benchmarks, license info, and serving recommendations before treating it as a production-ready model.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Qwen
Founded: 2023
China
qwenlm.github.io/blog/qwen3-coder/

Company Information

Alibaba
Founded: 1999
China
qwen.ai

Alternatives

Alternatives

Composer 1

Composer 1

Cursor
DeepCoder

DeepCoder

Agentica Project
Claude Fable 5

Claude Fable 5

Anthropic
Qwen3.6

Qwen3.6

Alibaba
Qwen2

Qwen2

Alibaba

Categories

Categories

Integrations

Alibaba Cloud
OpenClaw
Alibaba Cloud Model Studio
Brokk
Cline
Gemini
Gemini Enterprise
Hermes Agent
Model Context Protocol (MCP)
Nebius Token Factory
Novita AI
Odysseus
Ollama
OpenAI
Qwen
Qwen Studio
Qwen2.5
Shiori
SiliconFlow
Together AI

Integrations

Alibaba Cloud
OpenClaw
Alibaba Cloud Model Studio
Brokk
Cline
Gemini
Gemini Enterprise
Hermes Agent
Model Context Protocol (MCP)
Nebius Token Factory
Novita AI
Odysseus
Ollama
OpenAI
Qwen
Qwen Studio
Qwen2.5
Shiori
SiliconFlow
Together AI
Claim Qwen3-Coder and update features and information
Claim Qwen3-Coder and update features and information
Claim Qwen3.8-27B and update features and information
Claim Qwen3.8-27B and update features and information