LangGraph vs LLM Gateway
A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.
LangGraph Agents | LLM Gateway Agents | |
|---|---|---|
| Tagline | Stateful, graph-based agent orchestration from LangChain. | One API, 200+ models, transparent pricing, and no vendor lock-in. |
| Category | Agents | Agents |
| Pricing | Freemium· Free open-source; LangGraph Platform paid | Freemium· Bring Your Own Keys: Free / Credits: 5% flat fee on top of provider rates / Self-hosted: Free (AGPLv3) / Enterprise: custom |
| Model | BYO (Claude / GPT / open) | Routes to GPT-4o, Claude 3.5 Sonnet, Gemini 1.5, Llama 3.1, Mistral, and 200+ others |
| Editorial score | 8.8 / 10 | — |
| Use cases | stateful agentshuman-in-loopproduction | Multi-provider LLM routingAutomatic failover between model vendorsPer-model cost and token analyticsA/B testing prompts across GPT and ClaudePrompt-injection and PII guardrailsSelf-hosted AI gateway for regulated dataUnified API key managementVendor-agnostic AI agent backends |
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| Website | www.langchain.com | llmgateway.io |
Pick LangGraph if
- ✅ Reliable, debuggable agent graphs
- ✅ Built-in persistence + HITL
- ✅ Production-grade
- ✅ Tight LangSmith integration
Pick LLM Gateway if
- ✅ Single OpenAI-compatible endpoint fronts 40+ providers and 200+ models with a one-line base-URL change
- ✅ Automatic failover between providers keeps AI features up when a single vendor has an outage
- ✅ Real-time cost analytics broken down by model, provider, and route surface spend leaks early
- ✅ Bring-your-own-keys tier means you can adopt the routing and analytics without adding a middleman on billing