Benchmark profile
Terminal-Bench 2.0
A benchmark for agentic software engineering tasks executed in real terminal environments. DeepSeek reports it in the agentic section, while BenchLM also mirrors it in coding for models that publish it as a developer-task signal.
Data verifiedBenchmark score on Terminal-Bench 2.0 — July 23, 2026
BenchLM mirrors the published score view for Terminal-Bench 2.0. GPT-5.6 Sol leads the public snapshot at 91.9% , followed by Claude Mythos 5 (88.0%) and GPT-5.6 Terra (87.4%). BenchLM does not use these results to rank models overall.
GPT-5.6 Sol
OpenAI
gpt-5-6-sol
Claude Mythos 5
Anthropic
claude-mythos-5
GPT-5.6 Terra
OpenAI
gpt-5-6-terra
Benchmark score table (45 models)
ScoreThe published Terminal-Bench 2.0 snapshot places GPT-5.6 Sol first at 91.9%. The third row is 4.5 points behind. The broader top-10 range is 10.9 points, so the table still separates the published systems.
45 models have been evaluated on Terminal-Bench 2.0. The benchmark falls in the Coding category. This category carries a 20% weight in BenchLM.ai's overall scoring system. Terminal-Bench 2.0 is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About Terminal-Bench 2.0
Year
2026
Tasks
Terminal-based software tasks
Format
Interactive CLI agent evaluation
Difficulty
Professional software engineering
Terminal-Bench 2.0 focuses on realistic CLI and repository workflows rather than toy code generation. BenchLM keeps coding-category copies display-only unless the scoring weights include them.
BenchLM freshness & provenance
Version
Terminal-Bench 2
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
FAQ
What does Terminal-Bench 2.0 measure?
A benchmark for agentic software engineering tasks executed in real terminal environments. DeepSeek reports it in the agentic section, while BenchLM also mirrors it in coding for models that publish it as a developer-task signal.
Which model scores highest on Terminal-Bench 2.0?
GPT-5.6 Sol by OpenAI currently leads with a score of 91.9% on Terminal-Bench 2.0.
How many models are evaluated on Terminal-Bench 2.0?
45 AI models have been evaluated on Terminal-Bench 2.0 on BenchLM.
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