arXiv:2606.28480v1 Announce Type: cross Abstract: As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader range of general computer-use tasks beyond coding. However, existing benchmarks do not adequately evaluate general-purpose terminal computer-use agents (TUAs): general computer-use benchmarks primarily target graphical user interfaces (GUIs), whereas terminal-based benchmarks largely emphasize technical and programming-centric workflows historically native to the shell. We introduce TUA-Bench, a gen
The rapid advancement of large language models and agentic frameworks is driving the need for better benchmarks to evaluate their expanding capabilities in terminal environments.
This benchmark indicates significant progress in AI agents' ability to perform complex, general-purpose computer tasks beyond just coding, impacting white-collar automation.
The introduction of TUA-Bench provides a standardized way to measure and compare the performance of general-purpose terminal-use agents, accelerating their development and deployment.
- · AI agent developers
- · Automation software providers
- · LLM companies
- · Enterprise IT
- · Tasks requiring manual terminal operation
- · Human-centric desktop automation tools
Improved terminal-use agents will automate a broader range of IT and administrative tasks, increasing operational efficiency.
The automation of complex terminal workflows could redefine job roles that traditionally involve extensive command-line interface interaction.
As agents become more capable across diverse terminal environments, they could form the backbone of fully autonomous 'lights out' IT operations.
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Read at arXiv cs.AI