Multi-agent scaling can be compute-optimal: N parallel agents beat one agent run N-times longer
DimitrisPapail · x · 2026-09-22
Sharing data from ARC-AGI-3 ablations: for some problems, a team of N agents running 1x as long outperforms a single agent run for Nx as long — meaning multi-agent scaling is compute-optimal, not just speed-optimal. Anecdotally, a single agent with a bigger budget plateaus faster than best-of-N with 1/N budget each. Practical implication for parallel sampling vs. long single runs in agent engineering.
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