LangChain fits orchestration work such as prompt chains, tool use and agent architectures, while LlamaIndex fits connecting LLMs to your data through indexing, retrieval and RAG. Many AI products use both: LlamaIndex for data and LangChain for orchestration. The technical comparison of LangChain vs LlamaIndex below explains when to use each and how to combine them.
Technical comparison of LangChain vs LlamaIndex for AI products. When to use each and how to combine them.
LangChain is a general-purpose framework excelling at chaining prompts, tool use, and agent architectures.
LlamaIndex specializes in connecting LLMs to your data: indexing, retrieval, and RAG applications.
In practice, many AI products use both: LlamaIndex for data, LangChain for orchestration.
At SpeedMVPs, we select frameworks based on product requirements, not preferences.
LangChain and LlamaIndex are the two dominant LLM frameworks. This guide explains when to use each based on your product.
Side-by-side analysis.
Real-world cost comparison.
What can go wrong with each option.
How to choose for your case.
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Book a free 30-minute callSee our detailed comparison above. The right choice depends on your specific requirements, budget, timeline, and team capabilities.
Yes. Our scoping process includes technology and approach analysis. We recommend based on your specific situation, not preferences.
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