This model utilizes a Mixture-of-Experts architecture, featuring 480 billion total parameters with 35 billion active parameters per forward pass, distributed across 160 experts. Designed specifically for agentic coding, it excels at multi-step workflows, function calling, and tool use. By supporting deep repository-scale reasoning, it is built to assist developers in creating functional applications, positioning itself as a high-performance alternative to proprietary models in tasks like browser-use and foundational coding.

Developed through comprehensive pre-training and post-training stages, the model incorporates specialized function call protocols to enhance its utility in developer environments. It features 62 layers and a GQA attention mechanism, ensuring efficient performance during complex reasoning. With its ability to handle extensive token sequences, the model is optimized for long-context understanding, making it a robust choice for developers seeking to integrate advanced, agent-driven coding capabilities into their existing software workflows.