Humanity's Last Exam (with tools) leaderboard
17 models have a published score. Kimi K3.1 Pro (Moonshot AI) leads with 70.0, and the spread to the lowest score, Gemma 4 26B A4B at 17.2, is 52.8 points. An open-weight model leads here: Kimi K3.1 Pro at 70.0 is 2.3 ahead of the best closed model, Claude Opus 5.5. The highest-scoring model you can deploy on OpenLLM Buddy is DeepSeek V4.1 Flash, ranked 5 of 17 with 63.9. Sources report different settings for this test, such as test year, version, or reasoning effort. Each setting is listed in the source table, so compare close scores with care.
Humanity's Last Exam (with tools) scores
Exact-match accuracy, as with the no-tools version. Scores are not comparable with no-tools runs.
- OpenLLM Buddy catalog
- Open weights
- Closed API
- 1Kimi K3.1 ProHLE-Full (2,500 q), with tools, max effort (vendor-reported)70.0
- 2Claude Opus 5.5Humanity's Last Exam, with tools (web search/fetch, code execution); max effort67.7
- 3Claude Fable 5.1Humanity's Last Exam, with tools; max effort (Opus 5.5 system card lists Fable 5.1 at 65.6%)65.0
- 4Claude Sonnet 5.5Humanity's Last Exam, with tools; max effort64.5
- 5DeepSeek V4.1 FlashPass@1, with tools, max effort63.9
- 6GLM 5.3with tools62.5
- 7Muse Spark Openwith tools, xhigh effort61.0
- 8DeepSeek V4 ProV4-Pro-0813, with tools60.0
- 9Claude Haiku 5.5Humanity's Last Exam, with tools; max effort57.4
- 10GPT-6 AstraHumanity's Last Exam, with tools; max score at any effort57.2
- 11Kimi K3HLE-Full, with tools, max effort56.0
- 12GLM 5.3 Flashwith tools (page attributes to HF official evaluation section)55.3
- 13Reflection Beam 1.0with tools, BF1651.1
- 14Nemotron 3 Ultrawith tools37.4
- 15Gemma 4 31Bwith search26.5
- 16gpt-oss-120bhigh effort, with tools19.0
- 17Gemma 4 26B A4Bwith search17.2
What it measures
Labs rerun Humanity's Last Exam with the model allowed to search the web, run code, or call other tools. The toolset differs by lab and is noted next to each score where the source names it.
How it is scored
Exact-match accuracy, as with the no-tools version. Scores are not comparable with no-tools runs.
Why it matters
The gap between the tool and no-tool runs shows how much a model gains from acting as an agent.
Official benchmark pageMore agentic tests
Sources
Scores are published results from model cards, lab reports, and public leaderboards, each linked to its source. Settings such as thinking mode or test version differ between sources and are shown next to each score. OpenLLM Buddy catalog models are uncensored fine-tunes; their scores are those of the official base model. Data collected 2026-10-30. How the index works