Comparisons / Google ADK vs Smolagents

Google ADK vs Smolagents: Which Agent Framework to Use?

Google ADK vs Smolagents, head to head

Google ADK and Smolagents both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.

Google's Agent Development Kit (ADK) is an open-source framework for building multi-agent systems.

Smolagents is HuggingFace's minimalist agent library.

Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.

Pick Google ADK if

Pick Google ADK if aDK earns its complexity when you need multi-agent orchestration on Google Cloud with Vertex AI deployment. If you're using Gemini and need production-grade agent infrastructure, it's well-designed. For single-agent use cases or non-Google stacks, plain Python keeps things simpler. The tradeoffs in its intro should match how your team already thinks about agents; Smolagents will feel like translation if they don't.

Full Google ADKcomparison →

Pick Smolagents if

Pick Smolagents if smolagents lives up to its name — it's genuinely minimal and the code-agent approach is a real innovation that reduces LLM calls by ~30%. If you want a lightweight agent library with HuggingFace ecosystem access, it's excellent. For understanding the fundamentals, the plain version is even simpler. The tradeoffs in its intro should match how your team already thinks about agents; Google ADK will feel like translation if they don't.

Full Smolagentscomparison →

What both add

Whichever you pick, you're inheriting a dependency tree and a vocabulary your team has to learn before they ship anything. Google ADK has its own class hierarchy and tool registration conventions; Smolagents has its. Either way, when something misbehaves you'll be reading framework source before you reach the actual HTTP call.

If the real workload is one model and a handful of tools, both can feel like a workbench for driving a nail. The lesson below builds the same pattern in plain Python — useful as a comparison point even if you ultimately keep the framework.

By the numbers

By the numbers

Google ADK

GitHub Stars

18.7k

Forks

3.2k

Language

Python

License

Apache-2.0

Created

2025-04-01

Created by

Google

Backed by

Google/Alphabet

Cloud/SaaS

Vertex AI

Production ready

Yes

github.com/google/adk-python

Smolagents

GitHub Stars

26.4k

Forks

2.4k

Language

Python

License

Apache-2.0

Created

2024-12-05

Created by

Hugging Face

github.com/huggingface/smolagents

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptGoogle ADKSmolagents
Agent`LlmAgent` class with model, instructions, and `sub_agents` list`CodeAgent` or `ToolCallingAgent` with model and tools list
Tools`FunctionTool`, built-in tools (Search, Code Exec), third-party integrations`@tool` decorator or `Tool` class with name, description, and callable
Agent Loop`Runner.run()` with automatic tool dispatch and sub-agent delegationInternal loop: think (LLM reasons), act (code/tool call), observe (result)
Multi-AgentHierarchical agent tree with root agent delegating to specialized sub-agents
Workflows`SequentialAgent`, `ParallelAgent`, `LoopAgent` workflow primitives
SessionSession and State service with typed channels and persistence
Code Actions`CodeAgent` writes Python code as its action, executed in sandbox
SandboxE2B, Docker, Modal, or Pyodide sandbox for safe code execution
Model SupportHuggingFace Hub models, OpenAI, Anthropic, local via LiteLLM

Or build your own in 60 lines

Both Google ADK and Smolagents implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.

No framework. No dependencies. No opinions. Just the code.

Build it from scratch →