≈15.9approx. · 2.7× cost
≈12.3approx. · 3.4× cost
≈17.7approx. · 3.0× cost
≈35.5approx. · 10.5× cost
Can the model complete substantial programming work under this benchmark's agent setup?
One row per model, using its best reported score across effort settings.
| Rank | Model | Best score | Best reported setting |
|---|---|---|---|
| 1 | Claude Opus 5Anthropic | 43.3% | max effortAnthropic report1 value · 1 reportJul 24, 2026 · source |
| 2 | GPT-5.6 SolOpenAI | 34.4% | Reported configurationAnthropic report1 value · 1 reportJul 24, 2026 · source |
| 3 | Claude Fable 5Anthropic | 33.7% | Reported configurationAnthropic report1 value · 1 reportJul 24, 2026 · source |
| 4 | Claude Opus 4.8Anthropic | 21.1% | Reported configurationAnthropic report1 value · 1 reportJul 24, 2026 · source |
Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.
≈15.9approx. · 2.7× cost
≈12.3approx. · 3.4× cost
≈17.7approx. · 3.0× cost
≈35.5approx. · 10.5× cost
Can the model complete substantial programming work under this benchmark's agent setup?
Software implementation, debugging, or repository work under the published evaluation protocol. Higher is better. The value is the percentage reported in this lab's table.
This is a publisher-defined internal evaluation. The task set or grading details are not fully public, so treat it as directional evidence.
Internal run; mini-SWE-agent harness on GKE, mean reward over five attempts, with Opus 4.8 fallback on safety-classifier refusals for Opus 5 and Fable 5.
Method / source