Are you paying an AI swarm tax Stanford finds single agents can beat multi agent systems

Multi-agent wins often vanish when compute is matched equally

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.