Benchmarks / Agentic

EdgeBench

Uses the leaderboard's overall score at the longest (12-hour) environment-learning horizon. Score: 12-hour-horizon overall score. Collected by Jake Boggs' benchmark dashboard.

5models
–Open Index weight
–last updated
boggspublisher

EdgeBench

Higher is better · best effort per model

Chart settings
5 of 5 selected

full table below

#ModelEffortScoreCost / taskHarness
1Opus 4.8max51.3%––
2GPT-5.5xhigh48.4%––
3GPT-5.4xhigh39.3%––
4GLM 5.1max37.4%––
5DeepSeek V4 Promax31.0%––