Particle AI: particle-1

Particle AI: Particle-1 is an agentic coding model trained to handle software engineering work. It is post-trained on DeepSeek V4.1 Flash, which serves as its foundational architecture, and it is built to generate concise outputs suited to agentic coding workflows. It is Particle AI's first model. The model targets automated code generation, code refactoring, and bug fixing. Its main selling point is token efficiency: it uses roughly 45 percent fewer tokens on software engineering tasks than other models, which lowers costs for teams running large volumes of coding tasks and typically means faster generation times. Particle AI positions it as a token-efficient, cost-effective alternative in the AI coding model market. Because it is tuned for compact responses, Particle-1 fits best in agent loops and automated pipelines where every token counts. No public benchmark scores are available for the model, so evaluations should be based on your own coding workloads rather than published rankings.