We've pushed a version update to the Terminal-Bench dataset and leaderboard.
Terminal-Bench 4.0 calibrates task resources (time, cpu, memory), implements task fixes, and removes saturated tasks.
We're releasing Terminal-Bench-Science: a benchmark for evaluating AI agents on research workflows across scientific domains.
An ongoing Stanford-led community effort, built by the team behind Terminal-Bench together with scientific domain experts at research institutions
Introducing Terminal-Bench Challenges!
A new capability has emerged at the frontier: agents completing large-scale projects autonomously. To test this capability, we felt another flavor of benchmark was needed.
Terminal-Bench Challenges are long-horizon, token-intensive,
📣 Announcing Terminal-Bench Science: benchmarking AI agents on real scientific workflows – now open for task contributions👇
tbench.ai/news/tb-scienc…@AnthropicAI, @OpenAI, and @GoogleDeepMind use Terminal-Bench to evaluate AI on coding tasks. We're now extending it to
We're releasing Terminal-Bench 2.1 to patch 28 of the 89 tasks in Terminal-Bench 2.0
TB2.1 includes
• recalibrated limits
• fixed solutions
• realigned verifiers
Per-task breakdowns in 🧵
We'll continue to support TB2 and TB2.1 leaderboards (new submission process 🔜)