head to head · open source

Agno vs langgraph

Agno has 42,226 GitHub stars, 5,947 forks, 1,419 open issues and last shipped yesterday. langgraph has 41,863 stars, 7,069 forks, 786 open issues and last shipped today. Agno leads on adoption by 1% (42,226 vs 41,863 stars). Agno is written in Python under Apache-2.0; langgraph is written in Python under MIT. Agno has attracted 14% as many forks as stars, langgraph 17%. langgraph was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (agents, ai, ai-agents), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Agno ★ 42K langgraph ★ 42K category AI & Machine Learning

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Side by side

Agno langgraph
GitHub stars ★ 42K ★ 42K
License Apache-2.0 MIT
Written in Python Python
Last push 2026-09-17 2026-09-18
Forks ⑂ 5.9K ⑂ 7.1K
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agno if

  • You weight community size — 42K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full Agno profile →

pick langgraph if

  • You want the langgraph feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Python
  • You evaluated both and langgraph fits your workflow better

full langgraph profile →

About Agno

Agno is a model agnostic platform for building, running, and managing AI agent platforms. It provides both a Python SDK for agent development and a runtime environment (AgentOS) for serving agents as services, backed by a web based control plane. Agno lives in the Python based AI development ecosystem and targets teams seeking full ownership of their agent infrastructure without vendor lock in.

read the full Agno overview →

About langgraph

LangGraph is a low level Python orchestration framework for building stateful, long running agents, aimed at developers and platform teams who need durable execution, human in the loop control, and persistent memory instead of a turnkey agent application.

read the full langgraph overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

openclaw vs langgraph openclaw vs dify openclaw vs multica n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm hermes-agent vs opencode hermes-agent vs n8n openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all llama-cpp vs vllm

More AI Development Platforms projects

Compare either of these against the rest of the AI Development Platforms field.

Agno vs Dify Agno vs langchain Agno vs ponytail Agno vs generative-ai-for-beginners Agno vs graphify Agno vs claude-mem Agno vs ragflow Agno vs PaddleOCR Agno vs Agent-Reach Agno vs headroom Agno vs Mem0 Agno vs daily_stock_analysis

Frequently asked questions

Is Agno or langgraph more popular?

Agno has 42,226 GitHub stars and langgraph has 41,863. Agno has the larger community by that measure.

Are Agno and langgraph free?

Both are open source. Agno is licensed under Apache-2.0 and langgraph under MIT. Neither carries a licence fee.

What is the difference between Agno and langgraph?

Agno is written in Python and langgraph in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Agno or langgraph?

Choose Agno if you want the larger community (42,226 stars) or its Apache-2.0 licence terms. Choose langgraph if its feature set, stack or MIT licence fits better. Both are self-hostable.