Benchmarks / Reasoning

NanoGPT Speedrun

Uses Prime Intellect's source-reported share of the human record gap closed for each model's best validated optimizer-speedrun result. Score: share of the human record gap closed. Collected by Jake Boggs' benchmark dashboard.

18models
–Open Index weight
–last updated
boggspublisher

NanoGPT Speedrun

Higher is better · best effort per model

Chart settings
18 of 18 selected

full table below

#ModelEffortScoreCost / taskHarness
1Fable 5max81.7%––
2Opus 5max53.6%––
3Kimi K3max52.2%––
4Opus 4.8max39.4%––
5GPT-5.6 Solmax35.9%––
6GPT-5.6 Sol Promax33.6%––
7Sonnet 5max26.8%––
8GPT-5.6 Lunamax26.1%––
9Grok 4.5max24.6%––
10Qwen 3.8 Maxmax24.6%––
11GLM 5.2max20.3%––
12DeepSeek V4 Promax12.3%––
13GPT-5.6 Terramax11.0%––
14Grok 4.6max10.1%––
15Muse Spark 1.2max8.7%––
16Muse Spark 1.1max8.4%––
17GPT-5.5xhigh8.1%––
18Kimi K2.7none7.2%––