An open benchmarking framework to evaluate full AI agent systems across diverse tasks, measuring both performance quality and deployment cost.
- •Evaluates complete agent systems (tools, planning, memory, error recovery) rather than just models
- •Six unified benchmarks test different tasks: coding, customer service, technical support, personal assistance, and research
- •Results show general-purpose agents can match specialized ones, and agent architecture significantly impacts performance
- •Introduces Exgentic framework and standardized protocol for cross-environment evaluations
- •Open-weight models trail frontier models by 18-29 percentage points on average
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Hugging Face
Google Cloud