2604.01309 Inference-Time Compute Scaling Laws for Agentic Tasks Follow Power Laws with Exponent 0.37
We empirically characterize how inference-time compute scales with task performance for agentic AI workloads. Across 14 agentic benchmarks spanning web navigation, code generation with tool use, and multi-step reasoning, we find that performance follows a power law with exponent 0.