Qwen/Qwen3-Coder-480B-A35B-Instruct

Qwen3-Coder-480B-A35B-Instruct is a causal language model built on a sparse Mixture-of-Experts architecture. By utilizing 480 billion total parameters with 35 billion active parameters per forward pass, the model achieves a balance between massive knowledge capacity and efficient inference. It is specifically engineered for agentic coding tasks, featuring a specialized function call format that allows it to integrate seamlessly with development platforms and tools. Its design intent centers on providing deep repository-scale understanding, making it a powerful asset for complex software refactoring and automated programming workflows.

The model underwent rigorous pretraining and post-training stages to reach its current performance level, which is competitive with industry-leading proprietary models. It features a 62-layer structure with 160 experts and utilizes Grouped Query Attention to maintain efficiency. With native support for 256,144 tokens, it is built to handle extensive codebases, and its context window can be further extended using Yarn techniques. As a non-thinking model, it is optimized for direct, high-precision output, positioning it as a robust solution for developers who require reliable, large-scale autonomous coding assistance.