AG2 Framework vs Agency Swarm

Detailed side-by-side comparison to help you choose the right tool

AG2 Framework

🔴Developer

AI Automation Platforms

The next-generation AG2 platform with AgentOS runtime, framework interoperability, teachable agents, and enhanced planning for production multi-agent systems.

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Starting Price

Free

Agency Swarm

🔴Developer

AI Automation Platforms

Open-source Python framework that organizes AI agents into company-like hierarchies with strict communication channels. Built on the OpenAI Agents SDK. Free to use; you pay only for API calls to the LLM providers.

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Starting Price

Free

Feature Comparison

Scroll horizontally to compare details.

FeatureAG2 FrameworkAgency Swarm
CategoryAI Automation PlatformsAI Automation Platforms
Pricing Plans tiers tiers
Starting PriceFreeFree
Key Features

      AG2 Framework - Pros & Cons

      Pros

      • AgentOS runtime connects agents from AG2, LangChain, OpenAI, and Google ADK in one workflow
      • Teachable agents that improve over time without model retraining
      • Captain Agents dynamically spawn and manage sub-agent teams
      • Persistent memory preserves context across conversation sessions
      • Hosted platform available with a free tier for testing
      • Enhanced planning engine with pluggable algorithms for complex workflows
      • Backward compatible with all existing AutoGen and AG2 code

      Cons

      • Higher token consumption than structured task frameworks like CrewAI
      • Production readiness rated "medium" compared to LangGraph in independent reviews
      • Hosted platform execution limits (50/month free, 100/month for $25) don't include LLM costs
      • Community confusion about AG2 vs AutoGen vs Microsoft Agent Framework
      • Overkill for simple automation that doesn't need multi-agent coordination

      Agency Swarm - Pros & Cons

      Pros

      • Enforced communication hierarchy prevents agent chaos and reduces token waste
      • MIT license with no platform fees
      • Type-safe tools with Pydantic validation catch errors before API calls
      • ToolFactory converts any OpenAPI schema into agent tools
      • LiteLLM support opened the door to non-OpenAI models

      Cons

      • OpenAI models get the best experience; other providers feel second-class
      • Multi-agent workflows multiply API costs significantly
      • Fixed communication topology doesn't suit every workflow pattern
      • Smaller community than CrewAI or LangChain
      • Requires Python 3.12+ which excludes older environments

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