Pydantic AI vs OpenAI Agents SDK (Python)
Both are code-first Python agent libraries under MIT. Pydantic AI centers on typed agents: validated outputs, dependency injection and provider-prefixed model strings, with durable execution integrations and AG-UI built in. The OpenAI Agents SDK centers on handoffs, guardrails, sessions and built-in tracing, and integrates most closely with OpenAI's hosted tools and Responses API.
Facts side by side
| Fact | Pydantic AI | OpenAI Agents SDK (Python) |
|---|---|---|
| Type | Framework | Framework |
| Languages / SDKs | Python | Python |
| License | MIT | MIT |
| Pricing model | Open core | Open source, free |
| Orchestration pattern | Supervisor | Handoff |
| GitHub stars | 20,282 (as of 2026-09-30) | 29,784 (as of 2026-09-30) |
| GitHub forks | 2,831 | 4,837 |
| Last push | 2026-09-30 | 2026-09-30 |
| Latest release | v1.107.7 | v0.22.3 |
| Repository | pydantic/pydantic-ai | openai/openai-agents-python |
| Website | pydantic.dev | openai.github.io |
| Documentation | pydantic.dev | openai.github.io |
| Last verified | 2026-09-30 | 2026-09-30 |
| MCP support | Yes (checked 2026-09-30) | Yes (checked 2026-09-30) |
| A2A support | Partial (checked 2026-09-30) | No (checked 2026-09-30) |
| AG-UI support | Yes (checked 2026-09-30) | Unknown (checked 2026-09-30) |
| Install verified | 2026-09-30 | 2026-09-30 |
Choose Pydantic AI if
- You want outputs and tool arguments validated by Pydantic and visible to type checkers.
- You need durable execution on Temporal, DBOS, Prefect, Restate or similar engines.
- You need AG-UI support in the package, or frequent switching between model providers by model string.
Choose OpenAI Agents SDK (Python) if
- Your design is handoff-based: a triage agent passing the conversation to specialists.
- You want sessions with SQLite, Redis or SQLAlchemy backends and tracing included by default.
- You use OpenAI hosted tools, hosted MCP or sandbox agents.
Migration notes
Agents map one to one: instructions, tools and an output type exist on both sides. Handoffs in the OpenAI SDK become either agent delegation through a tool or programmatic hand-off in application code in Pydantic AI; graph-style flows use the separate pydantic-graph package. Approvals move between needs_approval=True (OpenAI) and deferred tools with requires_approval=True (Pydantic AI). Conversation storage differs: the OpenAI SDK has session backends, while Pydantic AI expects you to serialize message history yourself or add the separate pydantic-ai-harness package. Version notes: Pydantic AI V2 is a breaking release with a migration map, and 1.x is still maintained in parallel; the OpenAI SDK is on 0.Y.Z versions where minor releases can break interfaces. A2A is not built into either: Pydantic AI points to the external fasta2a package, and OpenAI maintainers do not plan an SDK-owned A2A layer.
FAQ
Can Pydantic AI use OpenAI models and the OpenAI SDK use other models?
Yes to both. Pydantic AI selects providers with a model string; the OpenAI Agents SDK README states support for 100+ other LLMs besides OpenAI's APIs.
Which has built-in tracing?
The OpenAI Agents SDK traces by default to OpenAI's dashboard or custom processors. Pydantic AI emits OpenTelemetry, which works with Logfire or any OTel backend.
Which supports AG-UI?
Pydantic AI ships an AG-UI adapter. For the OpenAI Agents SDK no official AG-UI support was found; the cell is unknown.