Stanford's LLM-as-a-Verifier: open model self-verification beats frontier closed models at 1/11 cost
jiqizhixin · x · 2026-09-05
A post claims Stanford's LLM-as-a-Verifier framework has DeepSeek V4 Flash generate 5 candidate agent trajectories, then validate, score, and rank them with the same model — no stronger closed model or external verifier — turning cheap open-source inference into a self-improving loop. Claimed results: Terminal-Bench 2.1 jumps from 79% to 88%, surpassing "Claude Fable 5" at 11x lower cost, with leads on Terminal-Bench V2 (86.5%) and SWE-Bench Verified (78.2%). Note: the model versions mentioned have no official releases; treat as unverified.
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