Agentic Frameworks for Reasoning Tasks: An Empirical Study
Recent advances in agentic frameworks have enabled AI agents to perform complex reasoning and decision-making. However, evidence comparing their reasoning performance, efficiency, and practical suitability remains limited. To address this gap, we empirically evaluate 22 widely used agentic frameworks across three reasoning benchmarks: BBH, GSM8K, and ARC. The frameworks were selected from 1,200 GitHub repositories collected between January 2023 and July 2025 and organized into a taxonomy based on architectural design. We evaluated them under a unified setting, measuring reasoning accuracy, execution time, computational cost, and cross-benchmark consistency. Our results show that 19 of the...
| Authors | Zeeshan Rasheed, Abdul Malik Sami, Muhammad Waseem et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 April 2026 |
| Last updated at source | 17 April 2026 |
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