The Harness Is Part of the Score
How a model's score on an agentic coding benchmark changes with the agent harness it runs in, from the labs' own per-harness reports.

Same model, different scores
Up to 8.2 points apart on one benchmark, by harness alone
Other labs report the same model under two harnesses, with gaps from none (GLM-5, Terminal-Bench 2.0) to 8.2 points (GLM-4.7). The same pair can swap order: Claude Code trails Terminus for GLM-4.7, ties it for GLM-5 and leads it for GLM-5.1 and GLM-5.2.

The harness moves Nemotron's score
Up to 13.5 points apart across six agent harnesses
NVIDIA ran Nemotron 3.5 Super in six agent harnesses: the harness moves its score by 8.4 points on SWE-bench Pro and 13.5 on Terminal-Bench 2.1. No harness is best on both: Claude Code leads on SWE-bench Pro, Codex on Terminal-Bench 2.1.

Which harness lifts a score
mini-swe-agent lower, own harness higher, Claude Code mixed
mini-swe-agent scored lower every time, by 0.2 to 7.1 points, and a lab's own harness higher every time, by 0.2 to 4.3, while Claude Code on other labs' models went both ways. Each pair is a different model and benchmark, so this shows direction, not a fixed effect.
Nemotron 3.5 Super: SWE-bench Pro by harness
Nemotron 3.5 Super: Terminal-Bench 2.1 by harness
SWE-bench Verified by harness
SWE-bench Pro by harness
| Model | Score | Sources |
|---|---|---|
| Qwen3.7-PlusQwen's own | 57.6% | Announcementlanguage benchmark table (first table), Coding Agent block, row 'SWE-Pro', column 'Qwen3.7-Plus'Run on the lab's own corrected version of the public set |
| Qwen3.7-PlusClaude Code | 55.8% | Announcementlater report: Qwen3.8-Flash-Next post, Language table (first table), row 'Agentic coding / SWE-bench Pro', column 'Qwen3.7-Plus'Run on the lab's own corrected version of the public set |
Terminal-Bench 1.0 by harness
Terminal-Bench 2.0 by harness
Terminal-Bench 2.1 by harness
DeepSWE v1.1 by harness
Tags
Nemotron 3.5 Super VL and Bolt on the timeline