Agno vs Google ADK
Side-by-side comparison of two agent options that often come up together when people are choosing between self-hosted frameworks, managed assistants, and extensible AI tooling.
Open source40k stars
Agno
High-performance multi-agent framework — build, run and manage teams of AI agents at scale
Open source19k stars
Google ADK
Google's open-source code-first Python toolkit for building and evaluating AI agents
Category
Agno
Google ADK
Tagline
High-performance multi-agent framework — build, run and manage teams of AI agents at scale
Google's open-source code-first Python toolkit for building and evaluating AI agents
Deployment
Self-hosted / Agno Cloud
Self-Hosted
Pricing
Open source and free to self-host. Agno Cloud available for managed deployments.
Free to use, with optional model or infrastructure costs if you self-host.
Channels
Web, api, CLI
Web, CLI
Open source
Yes
Yes
Privacy
Self-hosted deployments keep data on your infrastructure.
Some privacy controls exist, but vendor-hosted infrastructure still handles a meaningful share of the data flow.
Agno pros
- Extremely fast — benchmarks show 3x LangGraph speed.
- Native multi-agent team support built-in.
- Strong memory architecture with multiple storage backends.
Google ADK pros
- Official Google backing
- Built-in evaluation framework
- Multi-agent orchestration
Agno cons
- Developer-focused — no visual builder.
- Ecosystem smaller than LangChain/LangGraph.
- Requires Python knowledge.
Google ADK cons
- Python-only
- Development framework, not ready-to-use assistant
- Google Gemini API dependency
Agno gotchas
- Formerly called Phidata — old docs may use old name.
- Start with single agent before multi-agent orchestration.
Google ADK gotchas
- You should expect ongoing hosting, uptime, and secret-management work if you deploy it for real users.
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