AG2 vs LlamaIndex

Pick two tools from the same category to compare side-by-side.

	AG2 Community-maintained multi-agent conversation framework forked from Microsoft's AutoGen.	LlamaIndex Data framework for connecting LLMs to private data, with RAG, agents, and event-driven workflows.
Category	framework	framework
Vendor type	open source	hybrid
Pricing	free	freemium
Strengths	+ Proven conversational multi-agent patterns inherited from AutoGen + Open, contribution-based community governance + Built-in code execution and human-in-the-loop support + Model-agnostic across major LLM providers	+ Extensive data connectors and RAG tooling + Strong document parsing and ingestion (LlamaParse/LlamaCloud) + Agents and event-driven workflows built in + Large ecosystem and integrations
Tradeoffs	− Branding and lineage confusion with AutoGen and Microsoft Agent Framework − Still pre-1.0 with evolving APIs − Smaller institutional backing than vendor-led frameworks	− Broad API surface can be complex to navigate − Heritage is RAG-centric rather than agent-first − Frequent API changes across versions
Used in stacks	0	0