reasoning benchmark
Terminal-Bench-Science 0.1 is a Stanford-led community benchmark of 70 tasks drawn from scientific research workflows across the life, physical, earth, mathematical, and engineering sciences.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelOP | Score64.60% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelAN | Score52.60% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What Terminal-Bench-Science 0.1 measures and how its scores work.
It is a reasoning benchmark whose tasks are authored and reviewed by scientists and researchers.
It reports a Score in ratio units, typically as accuracy across the benchmark tasks.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about Terminal-Bench-Science 0.1.
GPT-6 Astra is currently ranked first with 64.60%.
The current leaders are GPT-6 Astra (64.60%) and Claude Fable 5.1 (52.60%).
GPT-6 Astra has the lowest matched official input price at $10 input / $50 output per 1M tokens.
The fastest matched records are GPT-6 Astra (30.66 tok/s via OpenAI) and Claude Fable 5.1 (7.67 tok/s via Anthropic).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It reports a Score in ratio units, typically as accuracy across the benchmark tasks.
Yes. Higher values rank better for this benchmark.
2 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis terminal-bench-science 0.1 AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
GPT-6 Astra currently leads Terminal-Bench-Science 0.1 with 64.60%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.