Qwen3-Coder

2025-07-22 · Publisher : Alibaba · Domain : Artificial Intelligence

Alibaba Qwen releases Qwen3-Coder-480B-A35B-Instruct, a MoE with 480 billion parameters (35 billion active) under Apache 2.0, dedicated to agentic coding, with the Qwen Code command-line tool.

What changes

  • Pre-training on 7.5 trillion tokens, 70% of which is code, with rewriting of noisy data by Qwen2.5-Coder.
  • Native context of 256,000 tokens, extensible to 1 million with YaRN, designed for entire repositories and pull requests.
  • Reinforcement learning on code ("hard to solve, easy to verify") followed by long-horizon agentic reinforcement, with 20,000 independent environments in parallel on Alibaba Cloud's infrastructure.
  • Results announced as state of the art among open models on SWE-Bench Verified without test-time scaling, and comparable to Claude Sonnet 4 according to the vendor.
  • Qwen Code tool, derived from Gemini CLI, and compatibility with Claude Code, Cline via a dedicated function-calling format.

### Context In mid-2025, coding agents (Claude Code, Gemini CLI) rely on models able to chain many tool calls. The vendor compares Qwen3-Coder to Claude Sonnet 4 and presents it as the "most agentic" of its coding models. ### What the model brings - Pre-training on 7.5 trillion tokens, 70% of which is code, with rewriting of noisy data by Qwen2.5-Coder. - Native context of 256,000 tokens, extensible to 1 million with YaRN, designed for entire repositories and pull requests. - Reinforcement learning on code ("hard to solve, easy to verify") followed by long-horizon agentic reinforcement, with 20,000 independent environments in parallel on Alibaba Cloud's infrastructure. - Results announced as state of the art among open models on SWE-Bench Verified without test-time scaling, and comparable to Claude Sonnet 4 according to the vendor. - Qwen Code tool, derived from Gemini CLI, and compatibility with Claude Code, Cline via a dedicated function-calling format. ### Architecture and specifications MoE with 480 billion total parameters and 35 billion active, 62 layers, 160 experts with 8 active, GQA with 96 query heads for 8 key-value heads. Non-thinking mode only. Native context 262,144 tokens. Apache 2.0 license. Weights on Hugging Face and ModelScope. Smaller versions followed, including Qwen3-Coder-30B-A3B (July 31, 2025). Knowledge cutoff: not disclosed. ### Cost and access | Context tier (qwen3-coder-plus, Alibaba Cloud API, current pricing consulted) | Input | Output | |---|---|---| | 0 to 32 K tokens | $1 | $5 | | 32 to 128 K | $1.8 | $9 | | 128 to 256 K | $3 | $15 | | 256 K to 1 M | $6 | $60 | Price per million tokens, USD. Self-hosting hardware not disclosed by the vendor. ### Benchmarks The comparisons (SWE-Bench Verified, Terminal-Bench, agentic tasks) appear as image charts in the post and the model card; no numeric table in text was found. No value is therefore reproduced here. ### Versus closed models The vendor claims that Qwen3-Coder achieves results comparable to Claude Sonnet 4 on agentic coding, browser use and tool use, and sets a new state of the art among open models on SWE-Bench Verified. These claims rely on vendor charts, whose values could not be verified in text. On costs, the vendor's API is priced by context tiers, with output at 5 dollars per million tokens for small requests, with no sourced comparison with closed APIs here. The full 480-billion-parameter model requires a multi-GPU infrastructure, which limits self-hosting, but the Apache 2.0 license allows commercial use without restriction. ### Key takeaways Qwen3-Coder is the milestone where Qwen enters the field of coding agents with an open model and tool. The comparison figures remain to be verified in the vendor's charts.

Links

Tags : LLM, Open Source, Alibaba, Qwen, MoE, Apache 2.0, Code