GPT Pilot vs LangGraph

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

	GPT Pilot Agents	LangGraph Agents
Tagline	Open-source multi-agent 'AI developer' that builds apps step by step with human checkpoints	Stateful, graph-based agent orchestration from LangChain.
Category	Agents	Agents
Pricing	Free· Free / open source (MIT). Users supply their own LLM API keys (OpenAI, Anthropic, Groq, Azure, or OpenRouter), so real cost depends on token usage on the chosen provider.	Freemium· Developer: $0 / seat per month · Plus: $39 / seat per month · Enterprise: Custom pricing
Model	Model-agnostic via OpenAI-compatible API (OpenAI GPT-4/4o, Anthropic Claude, Groq-hosted Llama, Azure OpenAI, OpenRouter)	BYO (Claude / GPT / open)
Editorial score	—	8.8 / 10
Use cases	greenfield full-stack app scaffoldingmulti-agent coding researchAI developer workflow prototypingself-hosted code generation with your own API keysteaching the phased agent patternCLI-driven project bootstrappingVS Code AI pair-programming experiments	stateful agentshuman-in-loopproduction
Pros	Multi-agent pipeline (Architect, Tech Lead, Developer, Reviewer, Debugger) that mirrors a real dev team rather than a single 'write code' prompt Human-in-the-loop checkpoints between tasks, so you can steer the build instead of babysitting a runaway autonomous loop Model-agnostic via OpenAI-compatible endpoints — works with OpenAI, Anthropic, Groq, Azure, and OpenRouter Ships as both a VS Code extension and a standalone CLI, with SQLite/Postgres state so long projects can be paused and resumed Fully open source (MIT), self-hostable, and one of the most-studied reference implementations of the phased-agent pattern	Reliable, debuggable agent graphs Built-in persistence + HITL Production-grade Tight LangSmith integration
Cons	Repository is no longer actively maintained — bug fixes, model updates, and new provider support have stalled Maintainers disclosed malicious code in the codebase from August 2025 through June 2026; anyone who ran it in that window must rotate API keys and audit outbound traffic Token costs on large projects add up quickly because the multi-agent loop re-reads context repeatedly across phases Generated code quality is heavily dependent on the underlying model; weaker models produce brittle scaffolding that needs substantial rework Not a hosted product — you install, configure, and supply your own keys, which is friction for non-developers	Steeper learning curve than CrewAI Verbose to set up
Website	github.com	www.langchain.com

Pick GPT Pilot if

✅ Multi-agent pipeline (Architect, Tech Lead, Developer, Reviewer, Debugger) that mirrors a real dev team rather than a single 'write code' prompt
✅ Human-in-the-loop checkpoints between tasks, so you can steer the build instead of babysitting a runaway autonomous loop
✅ Model-agnostic via OpenAI-compatible endpoints — works with OpenAI, Anthropic, Groq, Azure, and OpenRouter
✅ Ships as both a VS Code extension and a standalone CLI, with SQLite/Postgres state so long projects can be paused and resumed

Pick LangGraph if

✅ Reliable, debuggable agent graphs
✅ Built-in persistence + HITL
✅ Production-grade
✅ Tight LangSmith integration

Compare a different pair →