HSE SWE-bench Verified - Target Adaptation Claude Code: leaderboard

HSE v1 reports resolved rates on 500 SWE-bench Verified tasks and 113 DeepSWE tasks, using 3 runs. The default model is GLM-5.2 in the Pi or Claude Code harness. Its static library of 10 skills is evolved on SWE-Gym, with 8 success skills and 2 recovery skills. Gates 1–8 explicitly adapt to the target benchmark and remain distinct from frozen transfer. Cross-model GPT 5.5 and Opus 4.8 evaluations use Pi only. Model, harness, skill library, training scope, and gate identities are preserved. Metric: Resolved rate (%).

Metric: Resolved rate (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 8 models tracked.

Top models

#ModelScoreOverall rank
1HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate893.9
2HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate793
3HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate692.4
4HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate591.7
5HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate489.8
6HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate388.9
7HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate288.7
8HSE GLM-5.2 Claude Code SWE-bench Verified adapted Gate186.4

Interactive version: theaggregate.ai/benchmark?slug=hse-swe-bench-verified-target-adaptation-claude-code · How It Works · Data refreshed daily, snapshot 2026-10-28.