Terminal‑Bench 2.0 & Harbor: New Benchmark for Container Agents

Terminal‑Bench 2.0 and Harbor represent a coordinated leap forward for the AI‑agent community, addressing long‑standing pain points in reproducibility, task quality, and scalability. The benchmark, originally released in May 2025, quickly became the de‑facto standard for evaluating agents that operate via the command line, yet it suffered from inconsistent task specifications and external‑service dependencies. With 89 rigorously validated tasks that drop outliers like the unstable download‑youtube exercise, the new suite raises the difficulty ceiling while tightening reliability, ensuring that a model’s performance truly reflects its ability to navigate realistic developer workflows.

Harbor, the accompanying runtime framework, delivers the infrastructure needed to test those tasks at scale. By abstracting away the complexities of container orchestration, Harbor lets developers launch thousands of rollouts across major cloud providers such as Daytona and Modal with a single CLI command. Its API is agnostic to agent architecture, supporting supervised fine‑tuning, reinforcement learning pipelines, and custom benchmark deployments—all of which integrate seamlessly with Terminal‑Bench 2.0. The public leaderboard, powered by Harbor, currently showcases GPT‑5‑based agents leading the pack with a 49.6% task‑success rate, a close margin that underscores the competitive parity among top models.

The combined release not only standardizes how researchers evaluate agentic reasoning and code generation but also opens the door for a unified evaluation stack. By making high‑quality, container‑based testing accessible, Terminal‑Bench 2.0 and Harbor position themselves as foundational tools for the next wave of LLM‑driven software development, ensuring that progress can be measured, replicated, and accelerated across the ecosystem.