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A four-agent swarm uses twice the tokens but can cut elapsed time through parallelism
The cited analysis says a four-agent swarm used about twice the total tokens for the same performance, while parallel execution can reduce wall-clock time. It makes the token-versus-latency trade-off concrete when choosing multi-agent inference.
- What
- AI swarms are a form of inference scaling that can trade more tokens for less elapsed time.
- How
- A four-agent swarm used about twice the total tokens for the same performance, but parallel execution could cut task time in half.
- Why it matters
- Agent coordination adds a new factor in capability scaling that engineers and researchers need to track.
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