Compare Google ADK and Smolagents side by side. Both are tools in the Agent Frameworks category.
Updated March 10, 2026
Choose Google ADK if code-first approach enables testable, maintainable agent development.
Choose Smolagents if production-ready platform.
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| Category | Agent Frameworks | Agent Frameworks |
| Website | google.github.io | huggingface.co |
Key criteria to evaluate when comparing Agent Frameworks solutions:
Google's Agent Development Kit (ADK) is a flexible and modular framework launched in 2024 for developing and deploying AI agents using a code-first approach. The ADK was designed to make agent development feel more like traditional software development, enabling developers to create, deploy, and orchestrate agentic architectures ranging from simple tasks to complex multi-agent workflows. Available for both Python and TypeScript, ADK emphasizes writing clean, testable, and maintainable code rather than relying heavily on prompt engineering.
The framework's modular design enables developers to build specialized agents and compose them into hierarchical, scalable systems. ADK is not just a wrapper around language models but a comprehensive ecosystem for agent composition, workflow orchestration, behavior evaluation, and production deployment. The framework includes robust evaluation capabilities that help developers build trustworthy agents with clear feedback loops. TypeScript's type system makes data contracts between agents clear and robust, enhancing reliability in production environments.
While ADK offers deployment-agnostic capabilities that work with various hosting options, it is optimized for the Google Cloud ecosystem, particularly with Gemini models and Vertex AI. The open-source nature of ADK allows community contributions and evolution based on real-world usage. Developers appreciate ADK's structured approach, comprehensive evaluation framework, and software engineering principles, though teams working outside the Google ecosystem may find alternatives like Genkit more flexible for their needs.
AI platform providing comprehensive solutions for enterprise applications. The platform offers robust features for production AI deployment with focus on scalability, reliability, and developer experience. Suitable for teams building modern AI systems at scale.
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
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