Meet Harness-1: A 20B Retrieval Subagent Trained With Reinforcement Learning Inside a Stateful Search Harness on gpt-oss-20b
Quick Answer
Harness-1, a 20B retrieval subagent from UIUC and Chroma, utilizes reinforcement learning in a stateful search harness, achieving a 0.730 average curated recall across eight benchmarks, outperforming the next open subagent by 11.4 points.
Quick Take
The model's weights and harness code are publicly available.
Key Points
- Harness-1 is trained using reinforcement learning within a stateful search framework.
- It maintains a candidate pool, curated set, evidence graph, and verification records.
- Achieved 0.730 average curated recall, trailing only Opus-4.6.
- Publicly available weights and harness code enhance accessibility for researchers.
- Outperformed the next open subagent by 11.4 points across eight benchmarks.
Source Excerpt
Harness-1 is a 20B search agent reaching 0. 730 average curated recall across eight benchmarks, behind only Opus-4. 6.
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