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Terminal-Bench 2.0 tests whether AI agents can chain together the kind of multi-step, unsupervised terminal work a developer does in a day — compiling code, training models, setting up servers. Stanford's 2026 AI Index reports agent accuracy on it nearly quadrupled in a year, reaching 77.3% by early 2026, up from 20% in February 2025
Verified 2026-09-02
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More on Models
- Frontier AI models are catching up fast to benchmarks meant to resist them. A year ago they scored under 10% on Humanity's Last Exam, a 2,700-question test designed to be hard for AI and favorable to human experts. Now accuracy has reached 38.3% on Humanity's Last Exam, up from under 10% a year earlier
- AI agents attempting OSWorld's real-world computer tasks across Ubuntu, Windows and macOS — file operations, multi-app workflows — historically topped out at just 1% to 12% success. Stanford's 2026 AI Index reports the best model, Claude Opus 4.5, now reaches 66.3% accuracy, within 6 percentage points of the 72.35% human baseline 66.3% accuracy on OSWorld's real-computer-task benchmark
- Epoch AI's Capabilities Index scores frontier models on one aggregate scale, and fits a break in the trend at April 2024, when reasoning models and reinforcement learning took over frontier training. Before the break the frontier gained 8.3 index points a year; after it, 15.5 points a year, 1.85 times as fast