Benchmarks / Agentic

JobBench

Uses the first-party weighted-score leaderboard. Score: weighted score. Collected by Jake Boggs' benchmark dashboard.

21models
–Open Index weight
–last updated
boggspublisher

JobBench

Higher is better · best effort per model

Chart settings
21 of 21 selected

full table below

#ModelEffortScoreCost / taskHarness
1Opus 5max65.7%––
2Muse Spark 1.3max64.9%––
3Muse Spark 1.2max61.6%––
4GLM 5.3max61.4%––
5Fable 5max57.4%––
6Muse Spark 1.1max54.7%––
7Kimi K3max54.3%––
8Qwen 3.8 Maxmax52.7%––
9Opus 4.8max48.4%––
10GPT-5.6 Solmax45.4%––
11Opus 4.7max44.5%––
12GLM 5.2max43.4%––
13GPT-5.5xhigh38.3%––
14Sonnet 4.6max36.6%––
15GPT-5.4xhigh32.2%––
16Gemini 3.5 Flashxhigh31.5%––
17Inklingmax31.1%––
18Nemotron 3 Ultra 550B A55Bmax27.2%––
19GPT-5.2xhigh26.6%––
20Sonnet 4.5high20.7%––
21Gemini 3.1 Prohigh15.9%––