Harvey post-trains Qwen3.5 orchestrator: rubric pass rate jumps from 29.9% to 63%, beats Claude Code
SergioPaniego · x · 2026-09-09
Harvey published a blog post on post-training open-model agents for end-to-end M&A diligence. They trained a Qwen3.5-122B-A10B orchestrator, raising the rubric criteria pass rate from 29.9% to 63.0% on 50 held-out LAB Diligence data rooms — outperforming Claude Code and Codex, they claim.
Harvey's Tenet research preview emphasized model-harness co-optimization as key to complex legal tasks; this post is that approach applied in a real legal workflow. merve (Hugging Face) reshared it noting that post-training open-model agents is where the moat lies.
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