Comparisons / AWS Bedrock AgentCore vs Smolagents
AWS Bedrock AgentCore vs Smolagents: Which Agent Framework to Use?
AWS Bedrock AgentCore vs Smolagents, head to head
AWS Bedrock AgentCore 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.
Bedrock AgentCore is AWS's managed runtime for production agents, launched in July 2025.
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 AWS Bedrock AgentCore if
Pick AWS Bedrock AgentCore if agentCore is for production AWS deployments where you want to skip the runtime, memory, identity, and observability work and pay AWS to do it instead. It is framework-agnostic — bring Strands, LangGraph, CrewAI, or your own. For non-AWS teams, prototypes, or anything where you want to see what the agent is doing, plain Python on Lambda or a container is simpler. The tradeoffs in its intro should match how your team already thinks about agents; Smolagents will feel like translation if they don't.
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; AWS Bedrock AgentCore will feel like translation if they don't.
By the numbers
By the numbers
AWS Bedrock AgentCore
Managed service
Proprietary (AWS)
2025-07-16
AWS
Amazon Web Services
AgentCore Runtime, Memory, Identity, Gateway, Observability — pay-as-you-go on AWS
Yes
Used by: AWS internal teams, Amazon Q Developer
github.com/(closed-source SaaS — see strands-agents/* on GitHub for the SDK side)→Smolagents
26.4k
2.4k
Python
Apache-2.0
2024-12-05
Hugging Face
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | AWS Bedrock AgentCore | Smolagents |
|---|---|---|
| Runtime | Sandboxed, low-latency container per session, up to 8h, MicroVM-isolated | — |
| Memory | Managed short-term + long-term memory with semantic recall and namespacing | — |
| Identity | OAuth flows, AWS IAM, Secrets Manager integration, per-user credential vending | — |
| Gateway | Turn any API or Lambda into an MCP-compliant tool with one config | — |
| Observability | OpenTelemetry traces, per-step LLM call costs, error grouping in CloudWatch | — |
| Browser | Managed isolated browser tool for agent web actions | — |
| Agent | — | `CodeAgent` or `ToolCallingAgent` with model and tools list |
| Tools | — | `@tool` decorator or `Tool` class with name, description, and callable |
| Code Actions | — | `CodeAgent` writes Python code as its action, executed in sandbox |
| Sandbox | — | E2B, Docker, Modal, or Pyodide sandbox for safe code execution |
| Agent Loop | — | Internal loop: think (LLM reasons), act (code/tool call), observe (result) |
| Model Support | — | HuggingFace Hub models, OpenAI, Anthropic, local via LiteLLM |
Or build your own in 60 lines
Both AWS Bedrock AgentCore 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 →