Stanford research warns enterprises may be paying a “swarm tax” for multi-agent AI systems whose gains disappear under equal compute. When both single and multi-agent setups get the same “thinking token” budget, single agents usually match or outperform multi-agent architectures on multi-hop reasoning. Multi-agent approaches help mainly when context is corrupted or fragmented.
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