In 2024, we built single agents. In 2025, we are building Agent Swarms. But as we move from a single "doer" to a team of "collaborators," the token economics change drastically. A multi-agent system isn't just the sum of its parts; it includes the tax of coordination. Agents need to talk to each other, hand off tasks, and reach consensus. This "chatter" consumes tokens that don't directly produce end-user value but are essential for accuracy.

This post analyzes the cost implications of the three dominant orchestration patterns: Sequential, Hierarchical, and Voting/Consensus.

1. The Sequential Pattern (The Pipeline)

Structure: Agent A $\rightarrow$ Agent B $\rightarrow$ Agent C.

• Cost Profile: Linear.

• Overhead: Minimal. The output of A becomes the input of B.

• The Hidden Cost: Context Accumulation. By the time Agent C gets the prompt, it might be carrying the full history of A and B.

• Optimization: Implement Context Pruning at each handoff. Agent B should only pass the result to Agent C, not the entire thought process.

2. The Hierarchical Pattern (The Boss & Workers)

Structure: A "Supervisor" agent breaks down a goal and assigns sub-tasks to "Worker" agents.

• Cost Profile: Medium (1.5x – 2x single agent).

• The "Management Tax": The Supervisor consumes tokens planning and routing, but produces no final output itself.

• Efficiency Gain: Workers can use smaller, cheaper models (e.g., Llama 3.2 3B) because their tasks are narrowly scoped by the Supervisor (running GPT-4o).

• Verdict: This is the most cost-efficient pattern for complex tasks because it allows for Model Tiering—using expensive compute only for coordination.

3. The Voting / Consensus Pattern (The Debate)

Structure: Three agents generate answers independently, debate the differences, and vote on the best one.

• Cost Profile: Exponential (3x – 10x single agent).

• The "Debate Tax": If agents debate for 3 rounds, you pay for (3 agents $\times$ 3 rounds $\times$ Context Depth).

• ROI: Only viable for High-Stakes Reasoning (e.g., financial auditing, medical diagnosis) where the cost of an error is catastrophic.

• 2025 Benchmark: A "Majority Vote" pattern costs roughly 600% more than a single-shot prompt but increases accuracy on math benchmarks (like GSM8K) by 15–20%.

Architectural Takeaway: Do not default to Consensus patterns. Start with Hierarchical. Only pay the "Debate Tax" when the cost of failure exceeds the cost of compute.