Artificial Analysis Intelligence Index v3
MiniMax-M2 61.0 Dropped Version 3 of Artificial Analysis's index, ten evaluations that added agentic terminal and tool-use tasks to the knowledge, math and coding tests.
In use from 2 September to December 2025. Components: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, AIME 2025, SciCode, LiveCodeBench, IFBench, AA-LCR, Terminal-Bench Hard and τ²-Bench Telecom. Top models scored about 73.
Made by Artificial Analysis Released Sep 2025 Composite indices Last in a launch post Oct 2025 , dropped for a newer version
Last model added Oct 2025
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
1
Model scored in lab cards
2
Launch posts list it, from 2 labs
MiniMax-M2 leads with 61.0
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1 MiniMax-M2 61.0
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | MiniMax-M2 | 61.0 | Oct 2025 | Model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Reported by the lab in its model card
Labs moved on to Artificial Analysis Intelligence Index v4.0
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 27 Oct 2025 | MiniMax-M2 | 61 | AA Intelligence |
| 25 Sep 2025 |  Gemini 2.5 Flash | Artificial Analysis Intelligence Index (scatter chart, no printed value) |
Versions
More in Other
- Personal Superintelligence Index (Meta) In use Meta's composite of seven personal and knowledge-work evals: Agents' Last Exam, AutomationBench-AA, FocusBench, JobBench, GDP.pdf, VBT and DRACO.
- Anthropic ECI (AECI) Only in system cards Index that combines a basket of capability benchmarks into one capability score to track trends across Anthropic models. Claude Opus 5.5 169.4
- Qwen in-house English automatic evaluation Only in system cards Models answer Qwen in-house English datasets on knowledge, comprehension, coding, math and related skills. Skills and weights change between reports.
Qwen2-72B 72.9% - Recognition of model-written user turns (Anthropic) Only in system cards Models write synthetic user turns for real Claude Code transcripts, then judge which version is real. Score is accuracy above chance. Claude Mythos Preview 0.35
- LiveBench Dropped Models answer monthly refreshed questions across math, coding, reasoning, language, instruction following, and data analysis. Scored automatically against objective ground truth. Claude Fable 5.1 85.7%
- PhiBench Dropped Models answer original prompts that Microsoft's Phi team wrote to test a wide range of skills and reasoning.
Phi-4-Reasoning-plus 74.2%