SEC-Bench Pro
Can the model diagnose or complete difficult cybersecurity tasks?
Top rankings
One row per model, using its best reported score across effort settings.
| Rank | Model | Best score | Best reported setting |
|---|---|---|---|
| 1 | GPT-6 AstraOpenAI | 85.4% | Reported configurationOpenAI report1 value · 1 reportSep 3, 2026 · source |
| 2 | GPT-5.6 SolOpenAI | 79.1% | max effortOpenAI report1 value · 1 reportSep 3, 2026 · source |
| 3 | GPT-6 SolOpenAI | 66.3% | Reported configurationOpenAI report1 value · 1 reportSep 22, 2026 · source |
| 4 | GPT-6 LunaOpenAI | 34.2% | Reported configurationOpenAI report1 value · 1 reportSep 22, 2026 · source |
Effort curve
Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.
Definition and comparison boundarylimited methodology
Can the model diagnose or complete difficult cybersecurity tasks?
Security analysis or exploitation under a controlled evaluation environment. Higher is better. The value is the percentage reported in this lab's table.
Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.
OpenAI reports GPT-6 Astra 85.4%, GPT-5.6 Sol at Max 79.1%, GPT-6 Sol 66.3%, and GPT-6 Luna 34.2%. The card does not specify the harness or effort for the GPT-6 Sol/Luna rows.
Method / source