Hugging Face Agents vs smolagents vs Pydantic AI vs LangGraph

A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.

Hugging Face Agents Hugging Face's minimal library for code-writing agents Visit smolagents Hugging Face's minimalist agent library where agents write their actio... Visit Pydantic AI Type-safe Python agent framework built by the Pydantic team Visit LangGraph Open-source graph framework for durable, stateful AI agents Visit
RECATOOLS Score 6.6 / 10 7 / 10 8.2 / 10 8.3 / 10
Capability 6 8 8.5
Value for money 8 8.5 8
Ease of use 6 7.5 6
ASEAN readiness 5 6.5 6.5
API quality 6 8.5 8.5
Pricing Open Source Open Source Open Source Freemium
Free tier Fully free and open-source (Apache-2.0); works with any supported LLM backend.
Paid from
Has API
Open source
Free to use
Users 28K+ GitHub stars
Founded 2024
Maker Hugging Face
Verdict

smolagents' pitch is that an agent writing actual Python to call tools is more reliable than one emitting structured tool-call JSON that then gets parsed — Hugging Face claims roughly 30% fewer steps and LLM calls versus...

What this is for: Building lightweight AI agents that act by writing and running Python code in a sandbox. Who this is for: Developers who want a small, hackable agent framework with minimal abstractions and Hugging Fac...

Pydantic AI is the agent framework built by the team whose validation library already sits inside the OpenAI, Anthropic and Google SDKs, and that pedigree shows: structured output validation and dependency-injected testi...

LangGraph has genuine production mileage that most agent frameworks can only cite in a blog post: Klarna's customer-support assistant runs on it at 85 million users, Replit Agent's multi-step app-building flow is built o...

Full review → Full review → Full review → Full review →
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.