Open-Source AI · AI agent framework

AutoGen vs Agno

AutoGen vs Agno compared for 2026 — features, license, ease of use, performance and which one to choose. Microsoft's conversational agent framework vs Fast, lightweight multi-modal agents.

Updated regularly · curated by OpenSourceAI.tech

Choose AutoGen for researchers building conversational agent systems. Choose Agno for fast agents with memory and tools.

AutoGen vs Agno at a glance

SpecAutoGenAgno
CategoryAI agent frameworkAI agent framework
TypeMulti-agent frameworkAgent framework
LicenseMITMPL-2.0
Runs locallyCloud-optionalCloud-optional
Primary languagePythonPython
Ease of useAdvancedIntermediate
Best forresearchers building conversational agent systemsfast agents with memory and tools
GitHub stars60.1k41.5k

How AutoGen and Agno score

🤝 Too close to call — AutoGen and Agno land within a hair (3.9 vs 3.9 / 5). Pick on fit, not on score.
CriterionAutoGenAgno
Popularity4.54.0
Maintenance4.05.0
Ease of use2.53.5
Privacy3.53.5
License freedom5.03.5

Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.

What each one is

AutoGen

Multi-agent framework · MIT

AutoGen — the official full name, short for “Automated Generation” — is Microsoft’s open-source framework for building multi-agent AI systems where agents converse to solve tasks, with strong support for code execution and tool use.

  • Flexible multi-agent conversation patterns
  • Strong code-execution and tool-use support
  • Backed by Microsoft Research
See the AutoGen page →

Agno

Agent framework · MPL-2.0

Agno (formerly Phidata) is a lightweight, high-performance framework for building multi-modal agents with memory, knowledge and tools, plus a monitoring UI.

  • Very fast agent instantiation
  • Built-in memory, knowledge and tools
  • Multi-modal and model-agnostic
See the Agno page →

Key differences

AutoGen is multi-agent framework, while Agno is agent framework. Their licenses differ (MIT vs MPL-2.0), which matters if you ship a commercial product. AutoGen leans more advanced-friendly, whereas Agno is more suited to intermediate users. In short, AutoGen fits researchers building conversational agent systems, and Agno fits fast agents with memory and tools.

Which should you choose?

Choose AutoGen for researchers building conversational agent systems. Choose Agno for fast agents with memory and tools.

There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.

Frequently asked questions

Is AutoGen or Agno easier to use?

Agno is generally the easier of the two to get started with, while AutoGen rewards more setup with more control.

Are AutoGen and Agno free?

AutoGen is free and open source (MIT), and Agno is free and open source (MPL-2.0). Neither charges for the core software.

Can I run AutoGen and Agno locally?

AutoGen: cloud-optional · Agno: cloud-optional. Both can be used without sending your data to a third-party cloud where their setup allows.

AutoGen vs Agno — which should I pick in 2026?

Choose AutoGen for researchers building conversational agent systems. Choose Agno for fast agents with memory and tools.

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