📖 The AI Tool Bible

Gorilla vs LangGraph

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Gorilla
Agents
LangGraph
Agents
TaglineOpen-source LLM purpose-built for function calling and API invocation across thousands of tools.Stateful, graph-based agent orchestration from LangChain.
CategoryAgentsAgents
PricingFree· Free and Apache 2.0; self-hostedFreemium· Free open-source; LangGraph Platform paid
Modelgorilla-openfunctions-v2 (6.91B)BYO (Claude / GPT / open)
Editorial score—8.8 / 10
Use cases
function-callingtool-useapi-invocationagent-backbonerag-fine-tuning
stateful agentshuman-in-loopproduction
Pros
  • Fully open-source (Apache 2.0) with weights on HuggingFace
  • Purpose-trained for function calling, not a generic chat model retrofitted
  • Includes BFCL leaderboard as a public eval harness
  • GoEX runtime adds undo and damage-confinement for executed actions
  • Active Berkeley research backing with regular updates
  • Reliable, debuggable agent graphs
  • Built-in persistence + HITL
  • Production-grade
  • Tight LangSmith integration
Cons
  • Research project polish; not a managed SaaS
  • Smaller param count than frontier closed models
  • Self-hosting and ops are on you
  • Documentation skews toward papers and notebooks
  • Steeper learning curve than CrewAI
  • Verbose to set up
Websitegorilla.cs.berkeley.eduwww.langchain.com
Pick Gorilla if
  • ✅ Fully open-source (Apache 2.0) with weights on HuggingFace
  • ✅ Purpose-trained for function calling, not a generic chat model retrofitted
  • ✅ Includes BFCL leaderboard as a public eval harness
  • ✅ GoEX runtime adds undo and damage-confinement for executed actions
Pick LangGraph if
  • ✅ Reliable, debuggable agent graphs
  • ✅ Built-in persistence + HITL
  • ✅ Production-grade
  • ✅ Tight LangSmith integration
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