Model vs Harness - SWE-bench-45 Mean-of-4: leaderboard

Model vs Harness v1, four matched repetitions, all scheduled attempts included even if runtime fails; official task correctness differs from valid-completion rate. Harnesses: DeepAgents Code 0.1.3, OpenCode 1.15.6, Pi CLI 0.79.3, Codex CLI (unreported version). DeepSeek V4 Flash Preview official API; MiniMax M3, Kimi K2.7 Code, DeepSeek V4 Pro 0813 local SGLang on eight H200 GPUs. Qwen3.6-35B-A3B explicit HF checkpoint. Fixed GPT-5.5 xhigh native Codex subscription and DeepSeek V4 Pro 0813 native Harness SDK 0.1.0rc6 are complete-system references. No unreported reasoning effort inferred. All 45 Verified tasks with human-estimated difficulty >= 1 hour. Mean-of-4. Metric: Success rate (%).

Metric: Success rate (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 18 models tracked.

Top models

#ModelScoreOverall rank
1Model vs Harness DeepSeek-V4-Pro-0813 (Harness: DeepSeek Harness SDK 0.1.0rc6)70.56
2Model vs Harness GPT-5.5 (xhigh) (Harness: Codex CLI native)65.56
3Model vs Harness MiniMax-M3 (Harness: OpenCode 1.15.6)62.78
4Model vs Harness MiniMax-M3 (Harness: Pi CLI 0.79.3)52.22
5Model vs Harness Kimi-K2.7-Code (Harness: OpenCode 1.15.6)48.89
6Model vs Harness Kimi-K2.7-Code (Harness: Pi CLI 0.79.3)42.22
7Model vs Harness DeepSeek-V4-Flash-Preview (Harness: Codex CLI unspecified version)36.11
8Model vs Harness DeepSeek-V4-Flash-Preview (Harness: Pi CLI 0.79.3)35.56
9Model vs Harness DeepSeek-V4-Flash-Preview (Harness: OpenCode 1.15.6)32.22
10Model vs Harness DeepSeek-V4-Flash-Preview (Harness: DeepAgents 0.1.3)31.11

Interactive version: theaggregate.ai/benchmark?slug=model-vs-harness-swe-bench-45-mean-of-4 · How It Works · Data refreshed daily, snapshot 2026-10-27.