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Compare/LangGraph vs Pydantic AI

LangGraphvsPydantic AI

Generated from the two spec rows. Green marks the better value where a spec has a clear direction. Everything else is just different.

LangGraph
LangChain · Agent framework
OSSMCP
Panel
7.6
3 spec wins
Reliability
7.7
Usefulness
7.3
Cost
7.3
Longevity
8.0

“You do not need LangChain to use LangGraph, says the LangChain documentation.”

Pydantic AI
Pydantic · Agent framework
OSSMCP
Panel
8.0
2 spec wins
Reliability
8.0
Usefulness
7.7
Cost
8.3
Longevity
8.2

“From the people whose library already rejects your bad JSON, a framework that now rejects the model's as well.”

Spec by spec

SpecLangGraphPydantic AI
Architecture
CategoryAgent frameworkAgent framework
Runslocal, cloudlocal
Platformsmacos, linux, windowsmacos, linux, windows
Context windownot documentednot documented
Protocols
MCP clientYesYes
MCP serverYesNo
Capabilities
Runs terminal commandsNoYes
Multi-file editsNoYes
Git operationsNoNo
Browser controlYesNot in LangGraph itself: browser control comes from LangChain's own PlayWrightBrowserToolkit (Click, Navigate, ExtractText and related tools) in langchain-community, bound as agent tools. No
Sandboxed executionNoThe first-party langchain-sandbox package gave LangGraph agents a Pyodide/Deno PyodideSandboxTool but was archived in January 2026 with production use discouraged, so nothing current ships. No
Multi-agent orchestrationYesYes
Headless / CI modeYesYes
Models
Backboneany LangChain chat model, OpenAI, Anthropic, Ollamaany
Bring your own modelYesYes
Local modelsYesYes
Cost
Pricing modelbyokbyok
Starts at$0/mon/a
Free tierYesYes
Bring your own keyYesYes
Openness
Open sourceYesYes
LicenseMITMIT
GitHub stars42,59120,341

Which one would each critic pick

CriticLangGraphPydantic AIPick
El Juez——not enough reviews
El Amigo7.88.3Pydantic AI — Pick Pydantic AI if your team already writes typed Python and wants agents that fail at the type checker; pick LangGraph if the hard part is state rather than shape.
El Crítico7.37.5Pydantic AI — The complete coding agent, memory, sub-agents and context compaction all live in a separate harness package, so the advertised capability set is an assembly rather than an install.
El Profesor7.57.8Pydantic AI — Verification happens twice: outputs are parsed and validated by the same library that validates the rest of the codebase, and behaviour is asserted in the shape of pytest.
La Inversora7.87.8no preference
La Jefa7.08.0Pydantic AI — Traces leave over OTLP into the backend we already fund and the whole thing runs headless in our pipelines, so this is a dependency review rather than a purchase.
El Hacker8.39.0Pydantic AI — MIT, uv add pydantic-ai and I am running, the mcp extra on the slim distribution brings tool servers in, Ollama is a provider, and a test model needs no key at all.

Picks are derived from each critic's own scores. Humans vote on matchups on the duels page.

Want a third column? The compare tool handles any two agents. Three-way comparisons are on the roadmap once the spec rows are all verified.