Agno is a lightweight, high-performance framework for building multimodal agents with memory, knowledge and tools, previously known as Phidata.
Agno focuses on speed and simplicity: agents are plain Python classes, and the framework claims some of the lowest instantiation overhead in the ecosystem, which matters when you spawn many agents per request. It supports text, image, audio and video modalities within a single agent.
The stack includes built-in memory, knowledge bases with vector retrieval, structured outputs, tool use and a beautiful AgentOS interface for monitoring and control. Prebuilt agent teams and a marketplace of integrations help teams go from prototype to production without assembling every piece themselves. The AgentOS interface gives operations teams a live view of sessions, tools and memory, which matters once agents touch real customers. Its multimodal design also means one agent can handle voice notes, screenshots and documents in the same conversation.
Agno is open source and free for self-hosting. Agno’s managed platform charges for hosting and monitoring with a free developer tier, and enterprise subscriptions add support, security features and private deployment options. Self-hosting costs nothing beyond your own infrastructure, and managed pricing stays usage-based so early products are never over-committed.
Agno fits Python developers building multimodal assistants and high-volume agent services, from support automation to media processing pipelines. Teams that want a batteries-included framework without heavyweight abstractions find it a good balance. It also fits high-throughput services where agents are spawned per request and instantiation overhead directly affects response times.
Yes, the framework is free and open source. The managed platform provides a free tier for development and charges as hosted workloads scale.
Agno agents can be served behind your own API or hosted on Agno’s platform, which provides managed endpoints, session storage and usage analytics for production applications.
Agno differentiates on performance and multimodality versus more established frameworks. It is leaner than CrewAI and less infrastructure-focused than LangGraph, aiming at developers who want capable agents with minimal ceremony. Agno sits between minimalist libraries and heavy platforms, giving teams strong defaults for memory, knowledge and multimodality without imposing a large abstraction layer.
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