AI BriefingCheaper, More Powerful Patch Generation Through Collaboration Between Open Models and Frontier Models
Key point
By using a tiered architecture where a cheap model extracts context and a frontier model writes the final patch, the approach captures both cost efficiency and performance at the same time.
Details
The existing executor-orchestrator structure had frontier models doing the planning while smaller models handled execution, but this research redesigned the entire pipeline to maximize cost savings.
The new architecture works like a team. The Junior model (MiniMax-M3) explores the repository to locate where changes are needed, the Senior model (GPT-5.2) organizes key context such as relevant functions and tests, and finally the Principal model (Opus 4.8 or Fable 5) writes the exact patch in a single call based on the prepared brief.
This strategy achieved an 80.8% resolve rate on the SWE-Bench Pro benchmark. Compared to third-party hybrid approaches, this result lowers the cost per task to around $5.99 without sacrificing quality.
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