Cursor's Agent Swarm: Cheaper Models Handle Most Coding When Frontier Models Plan
The Decoder 1 month ago 7
Cursor built an agent swarm system that separates cheaper worker models from expensive frontier models used for planning, achieving 1,000 commits per second by dividing cognitive context between roles. In a Rust SQLite implementation benchmark, the hybrid approach (Opus planner with Composer 2.5 workers) scored 73–100 percent while costing $1,339 total, compared to $10,565 for GPT-5.5 running solo at similar quality. By using cheaper models for execution after frontier models establish plans, Cursor reduced codebase sizes by up to 85 percent and cut worker costs from $9,373 to $411 at comparable performance.