by open-compass · Agent Tool · ★ 142
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GTA: General Tool Agent Benchmark and Evaluation Framework [[NeurIPS 2024 D&B] GTA: A Benchmark for General Tool Agents](https://proceedings.neurips.cc/paperfiles/paper/2024/file/8a75ee6d4b2eb0b777f549a32a5a5c28-Paper-DatasetsandBenchmarksTrack.pdf) [[arXiv 2026] GTA-2: Benchmarking General Tool Agents from Atomic Tool-Use to Open-Ended Workflows](https://arxiv.org/pdf/2604.15715) ⬇️ Download Dataset Here: [GTA-Atomic] [GTA-Workflow] 🌟 Introduction GTA-2 is a benchmark and evaluation kit for General Tool Agents, designed to bridge atomic tool-use evaluation and open-ended workflow evaluation in one repository. Benchmark hierarchy GTA-Workflow: the new focus of GTA-2, for long-horizon, open-ended workflow evaluation. GTA-Atomic: the original GTA benchmark for short-horizon atomic tool-use tasks. Please refer to READMEGTA-1.md. This readme is centered around GTA-Workflow, which targets realistic long-horizon tasks with open-ended deliverables. Compared with traditional benchmark-style evaluation, GTA-Workflow focuses more on what an agent can finally accomplish in a complete workflow, rather than only whether it predicts the next tool
| Stars | 142 |
| Forks | 9 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 64.602976318854/100 |
| Last Updated | 2026-04-20 |
| Created | 2024-06-06 |
| Platforms | python |
| Est. Tokens | ~789k |
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GTA is [NeurIPS 2024 D&B] GTA: A Benchmark for General Tool Agents & [arXiv 2026] GTA-2. It is categorized as a Agent Tool with 142 GitHub stars.
GTA is primarily written in Python. It covers topics such as llm-agent, llm-evaluation.
You can find installation instructions and usage details in the GTA GitHub repository at github.com/open-compass/GTA. The project has 142 stars and 9 forks, indicating an active community.
GTA is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to GTA on Agent Skills Hub include Awesome-LLM-in-Social-Science, palico-ai, WebCanvas. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.