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Pydantic AI vs Agno

Agno is a Python agent framework that optimizes for breadth: a very large tool catalogue, teams, step workflows, and AgentOS to run and watch them. Pydantic AI gives you that breadth on a typed core with strict Pydantic validation: capabilities and the Harness SDK for the batteries, sub-agents for teams, pydantic-graph for workflows, and Pydantic Logfire to run and watch them.

Pydantic AI is one part of a stack: the Harness SDK for capabilities and complete agents, Pydantic Evals for evaluation, Pydantic Graph for graph-based workflows, Pydantic Logfire for observability, and Pydantic itself for validation. The tables below cover the whole of it.

Already built on Agno? The migrating-agno-to-pydantic-ai skill ports an existing application to Pydantic AI one working path at a time, preserving behavior rather than translating API names.

Framework

AgnoPydantic AI and Harness SDK
LanguagePythonPython
LicenseApache-2.0MIT
Model providersManyMany
ExtensibilityTools, toolkitsCapabilities and toolsets; 50+ with the Harness SDK
HarnessesBuild your ownBuilt-in Coder and Researcher, or compose your own
ObservabilityOpenTelemetryOpenTelemetry, including Pydantic Logfire
Durable executionYesSeven integrations
InterfacesAG-UI, A2A, chat platformsCLI, web chat, AG-UI, Vercel AI, ACP (experimental), GitHub Agentic Workflows
Realtime voiceNoRealtime
EvalsYesPydantic Evals
Image generationYesImage Generation

Features

AgnoPydantic AI and Harness SDK
Multi-agentYesSubagents, delegation, or pydantic-graph
PlanningTeams onlyPlanning
SkillsYesSkills
MemoryYesMemory
CompactionHistory window, session summariesCompaction
GuardrailsYesGuardrails
Code sandboxesYesExecution environments
Browser useYesWeb & research