reasoning benchmark
Terminal-Bench 2.1 is an updated release of the Terminal-Bench benchmark that tests AI agents' ability to operate a computer via the terminal. It evaluates how well models handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, data science workflows, and security tasks.
Updated Aug 7, 2026
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | OP | 88.8% | 100.0% | 17 | C | |
| 2 | MA | 88.3% | 93.8% | 17 | C | |
| 3 | OP | 87.4% | 87.5% | 17 | C | |
| 4 | AC | 86.6% | 81.3% | 17 | C | |
| 5 | OP | 84.7% | 75.0% | 17 | C | |
| 6 | AN | 84.3% | 68.8% | 17 | C | |
| 7 | XA | 83.3% | 62.5% | 17 | C | |
| 8 | DE | 82.7% | 56.3% | 17 | C | |
| 9 | ZA | 82.7% | 50.0% | 17 | C | |
| 10 | ME | 80.0% | 43.8% | 17 | C | |
| 11 | GO | 78.0% | 37.5% | 17 | C | |
| 12 | TE | 71.7% | 31.3% | 17 | C | |
| 13 | BY | 71.0% | 25.0% | 17 | C | |
| 14 | BY | 67.6% | 18.8% | 17 | C | |
| 15 | MI | 66.0% | 12.5% | 17 | C | |
| 16 | NV | 56.4% | 6.3% | 17 | C | |
| 17 | GO | 54.0% | 0.0% | 17 | C |
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.
Terminal-Bench 2.1 is an updated release of the Terminal-Bench benchmark that tests AI agents' ability to operate a computer via the terminal. It evaluates how well models handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, data science workflows, and security tasks.
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 Terminal-Bench 2.1.
GPT-5.6 Sol is currently ranked first with 88.8%.
Terminal-Bench 2.1 is an updated release of the Terminal-Bench benchmark that tests AI agents' ability to operate a computer via the terminal. It evaluates how well models handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, data science workflows, and security tasks.
Yes. Higher values rank better for this benchmark.
17 unique published model results are currently shown.
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.