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Single-Agent vs. Multi-Agent Systems: Total Cost of Ownership

As agent frameworks mature, developers transition from single-agent loops to multi-agent groups (using CrewAI or AutoGen) where agents communicate with each other. This increases capabilities, but also token consumption. Let's audit the economics of both designs.

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1. Communication Overhead in Multi-Agent Groups

In a single-agent system, the agent communicates only with the user and tools. In multi-agent systems, agents write to and read from each other. An "Editor Agent" critiques a "Writer Agent's" work, which sends paragraphs back and forth, creating large token exchange bills.

2. Token Math: CrewAI / AutoGen vs. Single Scripts

A single-agent task might use 10,000 tokens ($0.05). A multi-agent system executing the same task can run 15 inter-agent messages, pushing usage to 120,000 tokens ($0.60). Multi-agent designs scale operating expenses 5x to 12x.

3. When to Escalate to Multi-Agent Architectures

Avoid multi-agent groups for simple workflows. Use them only when tasks require distinct, conflicting roles (like code development and code review) where inter-agent critique is necessary to maintain output quality.

Frequently Asked Questions

Is CrewAI expensive to run?

CrewAI can be expensive in production if agents are set to run without strict loop limits. A single run can easily exceed 200,000 tokens if agents get stuck in discussion loops.

How do I lower multi-agent token consumption?

Set strict limit constraints, use compact system prompt instructions for each agent, and employ prompt caching on shared team briefings.