OpenAI’s GPT-6 Astra tops the Epoch Capabilities Index (ECI), our composite measure of model capabilities, with a score of 166, ahead of Anthropic’s Claude Fable 5.1 at 164 and OpenAI’s own GPT-5.6 Sol at 162. But this hides some complexity: while its Math-ECI of 170 sets a new record, on software engineering benchmarks Astra’s SWE-ECI of 164 still lags behind Fable 5.1’s 167.
| Model | Developer | ECI type | ECI | 90% CI lower | 90% CI upper | Benchmarks used |
|---|---|---|---|---|---|---|
| GPT-6 Astra | OpenAI | General ECI | 166.31 | 163.00 | 171.88 | 16 |
| Claude Fable 5.1 | Anthropic | General ECI | 164.47 | 161.36 | 168.28 | 15 |
| GPT-5.6 Sol | OpenAI | General ECI | 161.81 | 159.57 | 165.20 | 22 |
| Kimi K3 | Moonshot | General ECI | 157.63 | 155.38 | 160.45 | 19 |
| GPT-6 Astra | OpenAI | Math ECI | 169.83 | 165.98 | 175.37 | 4 |
| Claude Fable 5.1 | Anthropic | Math ECI | 165.73 | 162.84 | 175.91 | 4 |
| GPT-5.6 Sol | OpenAI | Math ECI | 162.76 | 159.85 | 166.24 | 4 |
| Kimi K3 | Moonshot | Math ECI | 158.39 | 155.23 | 162.76 | 4 |
| GPT-6 Astra | OpenAI | SWE ECI | 163.58 | 160.42 | 169.82 | 4 |
| Claude Fable 5.1 | Anthropic | SWE ECI | 167.44 | 161.95 | 178.53 | 3 |
| GPT-5.6 Sol | OpenAI | SWE ECI | 160.47 | 157.94 | 165.85 | 6 |
| Kimi K3 | Moonshot | SWE ECI | 161.54 | 158.59 | 165.87 | 5 |
| Snapshot | Snapshot date | Model | ECI | 90% CI lower | 90% CI upper | Benchmarks used | SWE benchmarks used | SWE benchmarks |
|---|---|---|---|---|---|---|---|---|
| At launch | 2026-09-03 | GPT-6 Astra | 169.23 | 164.85 | 174.02 | 9 | 1 | MirrorCode |
| Current | 2026-09-15 | GPT-6 Astra | 166.31 | 163.00 | 171.88 | 16 | 4 | MirrorCode; WeirdML; DeepSWE; FrontierCode |
| At launch | 2026-09-03 | Claude Fable 5.1 | 162.88 | 160.10 | 166.34 | 12 | 1 | FrontierCode |
| Current | 2026-09-15 | Claude Fable 5.1 | 164.47 | 161.36 | 168.28 | 15 | 3 | MirrorCode; WeirdML; FrontierCode |
Based on pre-release evals we gave Astra an ECI of 169 when it launched, but this fell as more software engineering benchmark results became available. Math-ECI and SWE-ECI are both domain-specific ECIs, refit on only one domain’s benchmarks, measuring a model’s strength relative to the general ECI. Explore these and custom subsets in our Domain-specific ECI Explorer.
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We compare four recent models (GPT-6 Astra, Claude Fable 5.1, GPT-5.6 Sol and Kimi K3) using the Epoch Capabilities Index (ECI), as well as domain-specific ECI variants meant to measure math and software capabilities. Domain-specific ECIs retain the benchmark difficulty parameters from the general ECI fit and re-estimate each model’s capability from only a subset of those benchmarks from a specific domain, making the resulting scores comparable to general ECI scores. See our domain-specific ECI documentation for details on methodology.
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