TUA-Bench: A Benchmark for General-Purpose Terminal-Use Agents
Summary
TUA-Bench is a comprehensive benchmark for evaluating general-purpose terminal-use agents across diverse digital activities and specialized workflows, revealing significant performance gaps among current frontier agents.
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Paper page - TUA-Bench: A Benchmark for General-Purpose Terminal-Use Agents
Source: https://huggingface.co/papers/2606.28480
Abstract
TUA-Bench presents a comprehensive benchmark for evaluating general-purpose terminal-use agents across diverse digital activities and specialized workflows, revealing significant performance gaps among current frontier agents.
As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader range of generalcomputer-use tasksbeyond coding. However, existing benchmarks do not adequately evaluate general-purpose terminal computer-use agents (TUAs): general computer-use benchmarks primarily targetgraphical user interfaces(GUIs), whereas terminal-based benchmarks largely emphasize technical and programming-centric workflows historically native to the shell. We introduce TUA-Bench, a general-purpose benchmark forterminal-use agents. TUA-Bench includes 120 real-world tasks across five task families, covering routinedigital activities-including document editing, email management, and live-web information seeking-as well as scientific and engineering workflows co-designed with PhD-level domain experts that requirespecialized software. This breadth distinguishes TUA-Bench from prior shell-focused or domain-specific benchmarks. Each task is manually designed, runs in a real terminal with a deterministic setup script, and is evaluated by anexecution-based scoring protocol. We find that the strongest frontier agent, Claude Code with Claude Opus 4.8 max reasoning effort, achieves 65.8% overall performance, with substantial gaps across both tracks. By providing a broad and realistic evaluation of terminal-use capabilities, TUA-Bench aims to accelerate the transition from narrow, task-specific assistants togeneral-purpose agentscapable of operating reliably across diverse digital environments.
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