Comparison Preset
Neither framework is a clear choice for an enterprise environment due to significant, opposing risks. SmolAgents is built on an enterprise-friendly Apache-2.0 license, but it currently has a CRITICAL known vulnerability, which is a major security and compliance concern. Conversely, AutoGen has no known vulnerabilities but uses a CC-BY-4.0 license, which presents legal challenges for commercial use and derivative works. Furthermore, AutoGen's slower recent development, with a commit frequency of less than once per week, introduces long-term support risk. A thorough risk assessment of SmolAgents' vulnerability and a legal review of AutoGen's license are required before either can be adopted.
Overview
The bottom line — what this framework is, who it's for, and when to walk away.
Bottom Line Up Front
AutoGen is a Python framework for building AI agents and applications, ranging from no-code prototyping to scalable, event-driven multi-agent systems. It supports conversational applications, complex workflows, and features like secure code execution and distributed agents.
SmolAgents is a Python library for rapidly building LLM agents with minimal code, emphasizing simplicity. It supports both code-writing agents with sandboxed execution and traditional tool-calling, integrating flexibly with various models and tools. Its design prioritizes ease of use and broad compatibility across modalities and sources.
Best For
Building scalable multi-agent AI systems, including business workflows and collaborative AI research.
Rapidly building and deploying LLM agents with code execution and flexible tool/model integration.
Avoid If
Requires an older Python version than 3.10.
no data
Strengths
- +Provides a web-based UI (AutoGen Studio) for no-code agent prototyping.
- +Features an event-driven core for scalable multi-agent AI systems and workflows.
- +Facilitates conversational single and multi-agent application development with AgentChat.
- +Enables secure code execution within Docker containers using built-in extensions.
- +Supports distributed agents and offers an extensible architecture for external services and community contributions.
- +Extremely easy to build and run agents with minimal code, designed for simplicity.
- +Supports Code Agents capable of writing actions in code, with secure sandboxed execution options (Modal, Blaxel, E2B, Docker).
- +Flexible integration with various LLM providers and models, including local Transformers and Ollama.
- +Agnostic to tool sources, allowing integration from MCP servers, LangChain, or Hugging Face Spaces.
- +Handles diverse input modalities beyond text, including vision, video, and audio inputs.
Weaknesses
- −Requires Python 3.10 or a newer version for AgentChat.
Project Health
Is this project alive, well-maintained, and safe to bet on long-term?
Bus Factor Score
Maintainers
Open Issues
Fit
Does it support the workflows, patterns, and capabilities your team actually needs?
State Management
AutoGen is an event-driven framework designed for conversational multi-agent systems, where state is managed through agent interactions and event flows.
no data
Cost & Licensing
What does it actually cost? License type, pricing model, and hidden fees.
License
Perspective
Your expertise shapes what we build next.
We build for engineers who make real architectural decisions. If something is missing, inaccurate, or could be more useful — we want to hear it.
FrameworkPicker — The technical decision engine for the agentic AI era.