AutoGen vs LlamaIndex
A side-by-side comparison of capabilities, autonomy, integrations, and pricing to help you choose.
Short answer: choose AutoGen if you want microsoft framework for multi-agent conversational ai applications (Supervised agent, free); choose LlamaIndex if you want open-source data framework for rag pipelines and data-grounded agents (Supervised agent, freemium).
| AutoGen | LlamaIndex | |
|---|---|---|
| What it is | Microsoft framework for multi-agent conversational AI applications | Open-source data framework for RAG pipelines and data-grounded agents |
| Type | framework | framework |
| Autonomy | Supervised agent | Supervised agent |
| Pricing | free · Free (open source) | freemium · Framework free (MIT); LlamaCloud has a free tier |
| Best for | developers, enterprise | developers, enterprise, mid-market |
| Deployment | self-hosted, api | self-hosted, api, saas |
| Modalities | text, code, api | text, code, api |
| Models | model-agnostic, gpt, claude, open-source | model-agnostic, gpt, claude, open-source |
| Protocols | function-calling, rest-api | function-calling, mcp, rest-api |
| Integrations | OpenAI, Azure OpenAI, Anthropic, Ollama | OpenAI, Anthropic, Pinecone, Qdrant, AWS Bedrock, Hugging Face |
| Capabilities | 4 documented | 4 documented |
AutoGen
- +Strong, well-known abstraction for multi-agent conversation (two-agent and group-chat patterns) from Microsoft Research
- +v0.4 rewrite brings an asynchronous, event-driven architecture with better observability and control
- +Open source, model-agnostic, and supports humans as first-class participants in agent conversations
- -Framework, not a product: autonomy and reliability depend entirely on what the developer builds
- -Now community-managed and described as in maintenance mode, with the original team's active work continuing under the renamed AG2 project
LlamaIndex
- +Best-in-class data and retrieval primitives (readers, indexes, retrievers, query engines) for grounding agents in your own data
- +Event-driven Workflows orchestrate multi-step agent processes with reflection and error-correction
- +Open source and model-agnostic, with LlamaCloud for managed document parsing and indexing
- -Framework, not a product: autonomy and quality depend entirely on what the developer builds
- -More oriented to data/RAG than to complex multi-agent orchestration compared with some peers
Which should you choose?
AutoGen is microsoft framework for multi-agent conversational ai applications, best for developers, enterprise. LlamaIndex is open-source data framework for rag pipelines and data-grounded agents, best for developers, enterprise, mid-market. The right choice depends on the autonomy level you want, your existing integrations, and your budget, all compared above.
This comparison is generated from the sourced AutoGen and LlamaIndex profiles. Open either profile to review its evidence and last-reviewed date.