Qwen3-Coder 30B-A3B Instruct

Qwen3-Coder 30B-A3B-Instruct is a causal language model built on a Mixture-of-Experts architecture, combining 128 expert neurons with a sparse activation scheme that fires only 8 of them during each forward pass. This design delivers the performance depth of a much larger model while keeping active computation lean—about 3.3 billion parameters working from a total pool of 30.5 billion. The model was engineered specifically for agentic coding workflows, supporting function-call formats compatible with popular development platforms and demonstrating strong performance on tasks like browser automation and repository-scale code comprehension. Its native long-context window allows it to ingest and reason across large codebases without losing thread, with extensions possible up to one million tokens using Yarn techniques for especially demanding analysis scenarios.

The model was produced through pretraining followed by targeted post-training, optimized for instruction-following without generating intermediate thinking blocks—making its outputs more direct and suited to production tool chains. Its open-weight status means developers can run, fine-tune, or deploy it in self-hosted environments, lowering barriers for teams building coding assistants or automation pipelines. Benchmark results position it well above average intelligence scores for comparable open-weight models, with particular strength in agentic and tool-use scenarios that demand reliable function calling. It pairs naturally with OpenAI-compatible APIs, enabling straightforward integration into existing code-generation workflows and coding agent platforms.