Qwen3 Coder 480B - Model Details

Qwen3 Coder 480B is a large language model developed by Alibaba Qwen, featuring 480 billion parameters and released under the Apache License 2.0 (Apache-2.0). It specializes in agentic software engineering tasks, leveraging advanced reinforcement learning to enhance its capabilities in autonomous coding and complex development workflows.

Description of Qwen3 Coder 480B

Qwen3-Coder-480B-A35B-Instruct, developed by Tongyi Lab, is a specialized code-focused large language model featuring 480 billion total parameters with 35 billion activated parameters via a mixture-of-experts (MoE) architecture. It achieves Claude Sonnet-level performance on foundational coding benchmarks and excels in agentic coding tasks, operating exclusively in non-thinking mode without generating <thinking> blocks. The model supports native 256K token context (262,144 tokens) and extends to 1M tokens using Yarn for repository-scale code understanding. Optimized for platforms like Qwen Code and CLINE, it employs a 62-layer causal language model with 96 query attention heads (GQA) and 160 total experts (8 activated), designed for efficient, autonomous software engineering workflows.

Parameters & Context Length of Qwen3 Coder 480B

Qwen3-Coder-480B leverages 480 billion parameters—placing it firmly in the very large model category (70B+), enabling exceptional complexity handling for agentic coding tasks while demanding substantial computational resources. Its 256K token context length (128K+), classified as very long context, allows seamless processing of entire code repositories and extended technical documentation, though it intensifies memory and latency requirements. This combination delivers industry-leading performance on coding benchmarks but necessitates optimized infrastructure for deployment.

• Parameter Size: 480b
• Context Length: 256k

Possible Intended Uses of Qwen3 Coder 480B

Qwen3-Coder demonstrates possible applications in automated code generation and explanation, where its agentic coding capabilities could assist developers in drafting or clarifying programming logic. It also presents potential uses for debugging and optimizing code, though these require careful validation to ensure reliability in real-world scenarios. Integration with development tools for automated code tasks represents another possible application, contingent on thorough testing within specific workflows. These potential uses must be rigorously evaluated before deployment, as their effectiveness depends on context-specific factors and system compatibility.

• code generation and explanation
• debugging and optimizing code
• integrating with development tools for automated code tasks

Possible Applications of Qwen3 Coder 480B

Qwen3-Coder offers possible applications in generating and explaining complex code snippets, where its agentic coding capabilities could support developers in drafting or clarifying logic. It presents potential uses for automated debugging and optimization of software, though these require rigorous validation to ensure accuracy. Possible integrations with development environments like IDEs or CI/CD pipelines for routine code tasks also exist, contingent on workflow-specific testing. Potential deployment in collaborative coding platforms for real-time suggestions is another possible application, but all scenarios demand thorough pre-use evaluation. Each application must be rigorously tested in context before implementation.

• code generation and explanation
• debugging and optimizing code
• integrating with development tools for automated code tasks
• collaborative coding platform suggestions

Quantized Versions & Hardware Requirements of Qwen3 Coder 480B

Qwen3-Coder (480B) in Q4 quantization requires professional-grade hardware due to its scale, typically needing multiple high-end GPUs (e.g., A100s or RTX 4090s) with 48GB+ total VRAM—not feasible for consumer graphics cards. This version balances precision and performance but demands significant infrastructure investment.

• fp16, q4, q8

Conclusion

Qwen3-Coder-480B, a 480-billion-parameter model with 35 billion activated parameters via mixture-of-experts architecture, delivers Claude Sonnet-level coding performance for agentic software engineering tasks while operating exclusively in non-thinking mode under Apache-2.0 license, supporting 256K native context length for repository-scale code understanding.

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