reasoning benchmark
Terminal-Bench 2.0
Terminal-Bench 2.0 is an updated benchmark for testing AI agents' tool use ability to operate a computer via terminal. It evaluates how well models can handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, security tasks, data science workflows, and cybersecurity vulnerabilities.
Updated Aug 11, 2026
Models49
Model coverage49
MetricScore
EvidenceC
Terminal-Bench 2.0 Ranking
Higher score ranks better on this benchmark.
Terminal-Bench 2.0 Score Distribution
A closer view of the leading scores on this benchmark.
Terminal-Bench 2.0 Highlights
The leading models and scores on this benchmark.
What is Terminal-Bench 2.0?
What Terminal-Bench 2.0 measures and how its scores work.
Terminal-Bench 2.0 is an updated benchmark for testing AI agents' tool use ability to operate a computer via terminal. It evaluates how well models can handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, security tasks, data science workflows, and cybersecurity vulnerabilities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of C.
- Family
- Terminal-Bench 2.0
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- terminal-bench-2|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Terminal-Bench 2.0.
Which model scores highest on Terminal-Bench 2.0?
GPT-5.5 is currently ranked first with 82.7%.
What does Terminal-Bench 2.0 measure?
Terminal-Bench 2.0 is an updated benchmark for testing AI agents' tool use ability to operate a computer via terminal. It evaluates how well models can handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, security tasks, data science workflows, and cybersecurity vulnerabilities.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
49 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.