Vals Terminal-Bench Science 0.1 (Terminal-Bench Science (Vals))
We show this table for reference; we do not rank on it.
Vals AI’s fixed-harness, single-trial run of 70 expert-authored scientific research workflows.
70-task pass@1 on Terminal-Bench Science (Vals) — September 22, 2026
We mirror the published 70-task pass@1 view for Terminal-Bench Science (Vals). GPT-6 Astra leads the public snapshot at 65.71%, followed by Claude Opus 5.5 (48.57%) and Claude Fable 5.1 (34.29%). We do not use these results to rank models overall.
GPT-6 Astra
OpenAI
max reasoning
Claude Opus 5.5
Anthropic
Claude Fable 5.1
Anthropic
29 modelsAgenticCurrentDisplay onlyUpdated September 22, 2026
70-task pass@1 table (29 models)
ScoreHow Vals Terminal-Bench Science mirror is shown here
BenchLM mirrors the public Vals AI Vals Terminal-Bench Science mirror leaderboard captured from https://www.vals.ai/benchmarks/terminal-bench-science and updated by Vals on September 22, 2026. The snapshot preserves overall scores, uncertainty, latency, cost-per-test metadata, and task-level scores where Vals publishes them.
Vals Terminal-Bench Science mirror is display only on BenchLM. Vals proprietary or Vals-hosted aggregate views are useful context, but BenchLM does not use them as weighted ranking inputs or as a replacement for benchmark-native source records.
Snapshot
The published Terminal-Bench Science (Vals) snapshot places GPT-6 Astra first at 65.71%. The third row is 31.43 points behind. The broader top-10 range is 55.71 points, so the table still separates the published systems.
29 models have been evaluated on Terminal-Bench Science (Vals). The benchmark falls in the Agentic category. We keep external benchmark mirrors separate from the weighted global scoring system, so these results remain source-specific evidence. Terminal-Bench Science (Vals) is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About Terminal-Bench Science (Vals)
Year
2026
Tasks
70 scientific research workflows across five domains
Format
Strict pass@1 accuracy
Difficulty
Expert scientific research workflows
Vals runs all 70 version-0.1 tasks through Terminus 2 and reports strict pass@1 by scientific domain. The fixed harness and single trial differ from the official native-agent, three-trial leaderboard; the Vals rows remain display-only and separate.
Freshness and provenance
Version
Terminal-Bench Science (Vals) 2026
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.
Questions
What does Terminal-Bench Science (Vals) measure?
Vals AI’s fixed-harness, single-trial run of 70 expert-authored scientific research workflows.
Which model leads the published Terminal-Bench Science (Vals) snapshot?
GPT-6 Astra currently leads the published Terminal-Bench Science (Vals) snapshot with 65.71% 70-task pass@1. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on Terminal-Bench Science (Vals)?
The September 22, 2026 snapshot contains 29 AI models.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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