Benchmarks / Reasoning

ClockBench

Uses the first-party analog-clock accuracy leaderboard. Score: overall accuracy. Collected by Jake Boggs' benchmark dashboard.

36models
–Open Index weight
–last updated
boggspublisher

ClockBench

Higher is better · best effort per model

Chart settings
36 of 36 selected

full table below

#ModelEffortScoreCost / taskHarness
1Opus 5.5max77.2%––
2GPT-6 Astramax75.0%––
3GPT-6.1 Solmax74.4%––
4GPT-5.6 Solmax68.3%––
5Gemini 3.8 Flashmax66.7%––
6Opus 5max65.5%––
7Fable 5.1max59.4%––
8Gemini 3.7 Flashmax53.3%––
9GPT-5.4high50.6%––
10GPT-5.5high46.1%––
11Muse Spark 1.3max42.2%––
12Qwen 3high39.4%––
13Fable 5max37.2%––
14Gemini 3.5 Flashxhigh34.4%––
15Gemini 3.1 Prohigh32.2%––
16Gemini 3 Prohigh31.1%––
17Grok 4.5max21.7%––
18Grok 4.6max20.0%––
19Gemini 2.5 Prohigh18.9%––
20GPT-5.2high15.6%––
21Opus 4.7max15.0%––
22o3 prohigh14.4%––
23o3high12.2%––
24Gemini 2.5 Flashmedium11.1%––
25GPT-5high11.1%––
26GPT-5 Prohigh11.1%––
27Mistral Medium 3.1none10.6%––
28Opus 4.6max10.0%––
29Opus 4.1high8.9%––
30GPT-5 Minihigh8.9%––
31Sonnet 4.5high7.8%––
32Sonnet 4high6.7%––
33GPT-4ohigh6.7%––
34Qwen 2.5–6.1%––
35GPT-5 Nanohigh3.9%––
36Grok 4 Fastnone3.3%––