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Pydantic AI vs OpenAI Agents SDK

The OpenAI Agents SDK is a small Python library built close to OpenAI’s own API: agents, handoff primitives, guardrails, and access to the hosted tools. Pydantic AI runs one typed Agent on any provider, with structured output validated by Pydantic and a Harness SDK of capabilities from sandboxes to sub-agents.

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

Framework

OpenAI Agents SDKPydantic AI and Harness SDK
LanguagePythonPython
LicenseMITMIT
Model providersOpenAI first; others via LiteLLMMany
ExtensibilityTools, guardrails, handoffsCapabilities and toolsets; 50+ with the Harness SDK
HarnessesSandboxAgent, or build your ownBuilt-in Coder and Researcher, or compose your own
ObservabilityOpenAI tracing, OTel via adaptersOpenTelemetry, including Pydantic Logfire
Durable executionYes5+ integrations
InterfacesREPL demo loopCLI, web chat, AG-UI, Vercel AI, ACP (experimental)
Realtime voiceYesRealtime
EvalsYesPydantic Evals
Image generationProvider-hosted tools onlyImage Generation

Features

OpenAI Agents SDKPydantic AI and Harness SDK
Multi-agentYesSubagents, delegation, or pydantic-graph
PlanningNoPlanning
SkillsYesSkills
MemoryYesMemory
CompactionYesCompaction
GuardrailsYesGuardrails
Code sandboxesYesExecution environments
Browser useBring your own ComputerWeb & research

FAQ

Can I build a coding agent on Pydantic AI? Yes. Give your agent the Coder() capability, or assemble your own from the same Agent; the harness repository has a complete coding agent built from the pieces Coder puts together.

Can I run my agents in CI? Yes. GitHub Agentic Workflows runs Pydantic AI agents from a Markdown workflow file in GitHub Actions, or run a Python script directly with uv run; nothing requires an Action.