Frontier-BenchBrowse 296

Frontier-Bench

Can the model complete substantial programming work under this benchmark's agent setup?

Version not specifiedExact reported variant
Coding4 ranked models4 reported values1 reportsHigher is better

Top rankings

One row per model, using its best reported score across effort settings.

4
RankModelBest scoreBest reported setting
1Claude Opus 5Anthropic43.3%max effortAnthropic report1 value · 1 reportJul 24, 2026 · source
2GPT-5.6 SolOpenAI34.4%Reported configurationAnthropic report1 value · 1 reportJul 24, 2026 · source
3Claude Fable 5Anthropic33.7%Reported configurationAnthropic report1 value · 1 reportJul 24, 2026 · source
4Claude Opus 4.8Anthropic21.1%Reported configurationAnthropic report1 value · 1 reportJul 24, 2026 · source

Effort curve

Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.

20
Anthropic · Anthropic reportClaude Fable 5

15.9approx. · 2.7× cost

EffortScoreCost/attempt
max33.7%$28.00
xhigh31.6%$20.00
high28.8%$14.60
medium24.8%$12.00
low17.8%$10.30
Anthropic · Anthropic reportClaude Opus 4.8

12.3approx. · 3.4× cost

EffortScoreCost/attempt
max18.8%$16.50
xhigh15.5%$12.50
high12.8%$8.00
medium9.5%$7.30
low6.5%$4.80
Anthropic · Anthropic reportClaude Opus 5

17.7approx. · 3.0× cost

EffortScoreCost/attempt
max43.2%$16.60
xhigh44.3%$14.70
high39.3%$11.60
medium34.8%$8.30
low25.5%$5.50
Anthropic · Anthropic reportGPT-5.6 Sol

35.5approx. · 10.5× cost

EffortScoreCost/attempt
max37.5%$11.50
xhigh29.0%$5.70
high22.5%$3.60
medium14.0%$2.60
low2.0%$1.10
Definition and comparison boundaryinternal methodology

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