Anthropic ECI (AECI)
Index that combines a basket of capability benchmarks into one capability score to track trends across Anthropic models.
Anthropic's adaptation of the Epoch Capabilities Index. The basket and weights are internal.
- Made by
- Anthropic
- Released
- April 2026
- Kind
- Composite indices
- Level
- Research frontier
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- Kept private
- Strongest model tested
- Claude Opus 5.5 #4 on the capability index
- Last in a system card
- October 2026
- Last model added
- October 2026
Claude Opus 5.5 leads with 169.4
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 Claude Opus 5.5 169.4
- 2 Claude Sonnet 5.5 167.9
- 3 Claude Haiku 5.5 167.1
- 4 Claude Opus 5 162.1
- 5 Claude Opus 4.8 155.5
- 6 Claude Opus 4.7 155.1
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Opus 5.5 | 169.4 | Sep 2026 | Lab model card | |
| 2 | Claude Sonnet 5.5 | 167.9 | Sep 2026 | Lab model card | |
| 3 | Claude Haiku 5.5 | 167.1 | Oct 2026 | Lab model card | |
| 4 | Claude Opus 5 | 162.1 | Jul 2026 | Lab model card | |
| 5 | Claude Opus 4.8 | 155.5 | May 2026 | Lab model card | |
| 6 | Claude Opus 4.7 | 155.1 | Apr 2026 | Lab model card |
4 models have held number one in labs’ own numbers since its release in April 2026
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs report it only in system cards
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.
7 system cards report it, from 1 lab
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Oct 7, 2026 | Claude Haiku 5.5 system card | 167.1 | Anthropic ECI (AECI), most recent fit (2.3.2) | AI R&D risk |
| Sep 28, 2026 | Claude Sonnet 5.5 system card | 167.9 | Anthropic ECI (AECI) on the most recent fit, 167.93 (2.3.2, Figure 2.3.2.A) | AI R&D risk |
| Sep 22, 2026 | Claude Opus 5.5 system card | 169.4 | Anthropic ECI (AECI), September 18 refit, 43 benchmarks, global 95% CI 165.23 to 177.05, local 167.99 to 171.24 (Table 2.3.5.3.A) | AI R&D risk |
| Jul 24, 2026 | Claude Opus 5 system card | 162.1 | Anthropic ECI (AECI) point estimate, 95% CI 158.0 to 167.3, n=40 benchmarks, earlier snapshot (2.3.3) | AI R&D risk |
| May 28, 2026 | Claude Opus 4.8 system card | 155.5 | Anthropic ECI (AECI) point estimate on a reduced set of 11 evaluations, between Opus 4.7 (154.1) and Mythos Preview (158.3) on the same set (2.3.4, Figure 2.3.4.A) | AI R&D risk |
| Apr 16, 2026 | Claude Opus 4.7 system card | 155.1 | Anthropic ECI (AECI), Claude Opus 4.7 at 155.1 with 95% CI 152.3 to 159.0, about 1.0 above the frontier trend through Opus 4.6, printed in chart legend (2.3.7, Figure 2.3.7.A) | AI R&D risk |
| Apr 7, 2026 | Claude Mythos Preview system card | Anthropic ECI (AECI), no AECI value printed for Mythos Preview. Slope ratios printed in the chart legend: 1.86 (break at Opus 4.5), 2.00 (Sonnet 4.5), 4.28 (Opus 4.6) (2.3.6, Figure 2.3.6.B) | AI R&D risk |
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.
- Artificial Analysis Intelligence Index v5 In use Version 5 of Artificial Analysis's index: nine evaluations in four equal categories, most with private test sets, run three times each in its own agent harness.
Gemini 4 Carbon 59.0
- SAGE v1.1 (Vals) In use Models grade handwritten undergraduate math and computer science work against rubrics. Scored by class-balanced accuracy of each rubric check against expert grading. Claude Opus 5.5 91.3%
- MTEB Fading Massive Text Embedding Benchmark: retrieval, clustering, classification across languages and modalities.
sonar 42%
- SPEED-Bench Only in system cards Measures speculative decoding across varied prompts and domains. Reports the average acceptance length of draft tokens, so higher means faster generation at the same output.
Nemotron 3 Ultra 5.15
- 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%