Agno

Agno: Python Framework for Multi-Agent Systems

Agno (formerly Phidata) is an open-source Python framework for building production multi-agent systems. The framework's distinguishing claim — backed by benchmarks — is that agents instantiate ~5000x faster than LangGraph and use ~50x less memory, making Agno suited for high-throughput agent deployments where LangGraph's overhead is a real cost.

18.5k+ GitHub stars and growing fast as the speed-and-simplicity alternative in the Python agent framework space.

Key Features

• 5000x faster agent instantiation vs LangGraph (per Agno benchmarks)
• 50x lower memory footprint
• Native multimodal: text, image, audio, video inputs
• Production primitives: sessions, tracing, scheduling, RBAC
• Open source with managed Agno Cloud option

Ideal Use Case

Engineering teams running agents at high throughput — customer support bots, research agents serving many users, agent systems where instantiation cost matters. Also fits teams that found LangGraph too heavy for their use case.

Why Use Agno

LangGraph won the durability/control angle; Agno's bet is on speed and simplicity. For teams whose agents need to start fast and run lean — particularly multi-agent products at scale — Agno's performance edge is meaningful.

FAQ

Q: Why was Phidata renamed to Agno? A: Rebrand in 2025 to align the company name with the agent framework focus.

Q: How does Agno compare to LangGraph? A: LangGraph emphasizes durable execution and graph-based control; Agno emphasizes speed and simplicity. Different use cases.

Q: Is Agno production-ready? A: Yes — sessions, tracing, scheduling, and RBAC ship in the framework, plus a managed Agno Cloud for hosted deployment.

tl;dr

Python multi-agent framework. 5000x faster agent instantiation than LangGraph. Native multimodal. Open source plus Agno Cloud.

Related

Looking for more options? Browse the Developer Tools directory or read our best AI coding tools listicle. Agno is also tracked on Crunchbase.