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Agno vs LangGraph

AgnoLangGraph

Bottom line: Agno for python teams building agents; LangGraph for engineering teams building production agents.

AgnoAgno

High-performance Python framework for building multi-agent systems and AgentOS

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LangGraphLangGraph

Graph-based orchestration for stateful, controllable LLM agents.

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Votes00
PricingFreemiumFreemium
CategoryAgent FrameworksAgent Frameworks
Tags
multi-agentpythonagentopsragopen-source
agentsorchestrationllm-frameworkopen-sourceworkflow
Best for
  • Python teams building agents
  • Teams wanting predictable flat pricing
  • Multi-agent system builders
  • Engineering teams building production agents
  • Developers needing controllable, resumable workflows
  • Teams already invested in LangChain
Pros
  • Performance-focused, Python-first design
  • Full local control plane free of charge
  • Flat pricing with no token or egress fees
  • Built-in knowledge, memory, and evals
  • Model-agnostic across major providers
  • Explicit, debuggable control over agent state and flow
  • MIT-licensed core, free to self-host
  • Model-agnostic, not tied to one LLM vendor
  • Strong support for cycles, checkpointing, and human-in-the-loop
  • Backed by the widely used LangChain ecosystem
Cons
  • Python-only framework
  • Pro plan starts relatively high at $150/month
  • Additional connections and seats add up
  • Rebrand from Phidata may cause some confusion
  • Ecosystem younger than the largest frameworks
  • Steeper learning curve than high-level agent builders
  • Requires comfort with graph and state concepts
  • Paid platform and observability are separate products
  • Documentation and APIs have evolved quickly
  • Can be overkill for simple single-shot LLM tasks

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