I Made My Evals Replay Every Task on a Local Model. The Frontier Lead Got Thin.
My agents run on frontier models, but a free local model sits idle on a Mac Mini in my office. So I wired my eval system to replay every writing task on the local model and grade both. Across 10 like-for-like rematches the local model reached statistical parity — and beat the frontier model outright on four of them. Here is the receipts-first system that made it prove it.
My agents do real work on frontier models. Every dollar of that work is metered against my OpenAI and Anthropic bills. Meanwhile a perfectly capable local model, gpt-oss:20b, sits on a Mac Mini in my office costing me nothing. The obvious question: for which tasks could the free local model do the job just as well?
