Agno vs Letta
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 source22k stars
Letta
Platform for building stateful agents with advanced memory persistence
Category
Agno
Letta
Tagline
High-performance multi-agent framework — build, run and manage teams of AI agents at scale
Platform for building stateful agents with advanced memory persistence
Deployment
Self-hosted / Agno Cloud
Self-Hosted
Pricing
Open source and free to self-host. Agno Cloud available for managed deployments.
Usually affordable for individuals or small teams, with some recurring model or hosting costs.
Channels
Web, api, CLI
Telegram, Slack, Discord, WhatsApp, Signal
Open source
Yes
Yes
Privacy
Self-hosted deployments keep data on your infrastructure.
Good privacy posture for most teams, especially when self-hosted or carefully configured.
Agno pros
- Extremely fast — benchmarks show 3x LangGraph speed.
- Native multi-agent team support built-in.
- Strong memory architecture with multiple storage backends.
Letta pros
- Open source with transparent code and flexible deployment options.
- Strong privacy story for users who care where data runs.
- Good memory and persistence support for ongoing conversations or tasks.
Agno cons
- Developer-focused — no visual builder.
- Ecosystem smaller than LangChain/LangGraph.
- Requires Python knowledge.
Letta cons
- Lower autonomy — designed more as a platform than an out-of-box assistant
- Setup requires understanding memory architecture concepts
- Python-only — no native TypeScript/JavaScript implementation
Agno gotchas
- Formerly called Phidata — old docs may use old name.
- Start with single agent before multi-agent orchestration.
Letta gotchas
- You should expect ongoing hosting, uptime, and secret-management work if you deploy it for real users.
- Recurring subscription or model spend can matter more than the headline feature list.
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