Frontier AI at a fraction of the cost: open-source workers with a closed-source advisor

An open-source worker model combined with a closed-source advisor model has demonstrated improved outcomes at reduced costs across three benchmarks, including software engineering, terminal operations, and legal work. This setup uses an open-source model (Kimi-K2.6 or GLM-5.2) to handle tasks end-to-end while consulting a closed-source frontier model (Claude Opus 4.8) for review, resulting in higher success rates and cost efficiency. The advisor model only provides feedback during a single review step and cannot edit files, allowing the worker to maintain control over task execution. The study found that using an advisor increased task resolution rates with minimal additional costs, with GLM-5.2 plus advisor reaching parity or surpassing Opus as a worker in certain benchmarks at a fraction of the cost. The findings indicate the potential for scalable deployment of this worker-advisor configuration, highlighting its robustness and efficiency without the need for per-model or per-benchmark tuning.

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