Terminal-Bench 2.0 Launches Alongside Harbor, a New Framework for Testing Agents in Containers

Why It Matters

By delivering a higher‑quality benchmark and a production‑grade evaluation stack, the release lets researchers and developers reliably compare, fine‑tune, and deploy AI agents, accelerating their adoption in developer‑centric and operational workflows.

Summary

Terminal-Bench 2.0 was launched with 89 rigorously validated, more difficult tasks, addressing inconsistencies of the original suite and setting a new standard for evaluating autonomous AI agents in terminal environments. The accompanying Harbor framework enables large‑scale, container‑based rollouts across major cloud providers, supporting any agent, supervised fine‑tuning and reinforcement‑learning pipelines, and seamless integration with the new benchmark. Early leaderboard results show OpenAI’s Codex CLI (GPT‑5) leading with a 49.6% success rate, though no model solves more than half the tasks. Together, the benchmark and framework aim to become the de‑facto infrastructure for reproducible, scalable agent testing and optimization.