Mastra vs LangChain: AI Agent Pipeline Comparison
langchain•Jun 13, 2026

Mastra vs LangChain: AI Agent Pipeline Comparison

In this article, we compare Mastra and LangChain, two popular AI frameworks used to build agent pipelines. We'll explore their differences and similarities through a real-world example, including a five-step research and synthesis pipeline, and discuss the results of our benchmarking tests.

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Key summary

A comparison of Mastra and LangChain, two AI frameworks used to build agent pipelines, highlighting their differences and similarities through a real-world example.

TL;DR

  • Mastra and LangChain are two AI frameworks used to build agent pipelines.
  • Mastra uses a workflow with typed step contracts, while LangChain uses a directed graph with plain async functions.
  • LangChain promises leaner execution and more explicit control over model calls.
  • We built the same pipeline in both frameworks and measured tokens per step, latency, and other metrics.
  • Our benchmarking tests showed significant differences in token overhead and latency between the two frameworks.
  • We also built a real-time web dashboard to visualize the decision-making process of both frameworks.

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