agents benchmark
FrontierSWE measures whether an agent can complete open-ended technical projects at the scale of hours to tens of hours, spanning systems optimization, large-scale code construction, and applied ML research. Performance is reported as a dominance score, where higher is better.
Updated Aug 7, 2026
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | AN | 90.0% | 100.0% | 15 | B | |
| 2 | MA | 81.2% | 92.9% | 15 | C | |
| 3 | AN | 75.0% | 85.7% | 15 | B | |
| 4 | ZA | 74.0% | 78.6% | 15 | B | |
| 5 | AC | 73.5% | 71.4% | 15 | C | |
| 6 | OP | 73.0% | 64.3% | 15 | B | |
| 7 | AN | 63.0% | 57.1% | 15 | B | |
| 8 | AN | 56.0% | 50.0% | 15 | B | |
| 9 | OP | 54.0% | 42.9% | 15 | B | |
| 10 | GO | 40.0% | 35.7% | 15 | B | |
| 11 | ZA | 31.0% | 28.6% | 15 | B | |
| 12 | DE | 29.0% | 21.4% | 15 | B | |
| 13 | MA | 27.0% | 14.3% | 15 | B | |
| 14 | MA | 26.0% | 7.1% | 15 | B | |
| 15 | AC | 22.0% | 0.0% | 15 | B |
Top published rows on the benchmark's original scale.
The top published results on this benchmark's own scale.
Definition and scoring fields from the benchmark registry.
FrontierSWE measures whether an agent can complete open-ended technical projects at the scale of hours to tens of hours, spanning systems optimization, large-scale code construction, and applied ML research. Performance is reported as a dominance score, where higher is better.
Scores are shown in ratio. The current registry marks this benchmark as not independently verified with evidence level B.
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
Common questions about FrontierSWE.
Claude Fable 5 is currently ranked first with 90.0%.
FrontierSWE measures whether an agent can complete open-ended technical projects at the scale of hours to tens of hours, spanning systems optimization, large-scale code construction, and applied ML research. Performance is reported as a dominance score, where higher is better.
Yes. Higher values rank better for this benchmark.
15 unique published model results are currently shown.
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.