Pydantic AI vs Google ADK
Google’s Agent Development Kit is an agent platform built around Gemini and Vertex AI: workflow graphs, evaluation, a dev UI, and deploy commands for Cloud Run, GKE, Docker and Agent Engine. Pydantic AI is a provider-agnostic library you run on your own infrastructure, with pydantic-graph for workflows, Pydantic Evals, a web chat UI, and Pydantic Logfire to watch it all run.
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.
| Google ADK | Pydantic AI and Harness SDK | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | MIT |
| Model providers | Gemini first (LiteLlm, AnthropicLlm exist) | Many |
| Extensibility | Tools, plugins | Capabilities and toolsets; 50+ with the Harness SDK |
| Harnesses | Build your own; shell, file tools, sandboxes and compaction ship | Built-in Coder and Researcher, or compose your own |
| Observability | OpenTelemetry | OpenTelemetry, including Pydantic Logfire |
| Durable execution | Yes | 5+ integrations |
| Interfaces | CLI, web, A2A | CLI, web chat, AG-UI, Vercel AI, ACP (experimental) |
| Realtime voice | Yes | Realtime |
| Evals | Yes | Pydantic Evals |
| Image generation | No | Image Generation |
| Google ADK | Pydantic AI and Harness SDK | |
|---|---|---|
| Multi-agent | Yes | Subagents, delegation, or pydantic-graph |
| Planning | Prompt-level only | Planning |
| Skills | Yes (experimental) | Skills |
| Memory | Yes | Memory |
| Compaction | Yes | Compaction |
| Guardrails | Yes | Guardrails |
| Code sandboxes | Yes | Execution environments |
| Browser use | Yes | Web & research |
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.