LLM gateway basics ยท 2026-05-23

AI gateway vs LLM gateway: model access, security, and cost control

Compare AI gateway and LLM gateway architecture across model access, OpenAI-compatible APIs, security, API keys, usage metering, and cost control.

Diagram comparing AI gateway and LLM gateway layers across applications, model providers, security, and cost controls.

AI gateway is the broader category

AI gateway describes a control layer for traffic to text, image, embedding, audio, video, agent tools, and other AI services.

That layer often handles authentication, usage metering, rate limits, cost visibility, and security policies.

LLM gateway focuses on language-model traffic

LLM gateway is more specific: it manages standard APIs, model catalogs, routing decisions, token costs, context windows, and error shape for large language model requests.

For many product teams, this is the immediate need: keep one OpenAI-compatible client while switching between GPT, Claude, Gemini, or another model.

  • AI gateway: broader AI traffic umbrella.
  • LLM gateway: language-model and token-based usage layer.
  • LLMTR: a platform that combines OpenAI-compatible LLM access with AI gateway needs.

Security and data control matter

Gateway choice should not be based only on provider count. API key scope, prompt body policy, usage logs, rate limits, and error visibility matter more in production.

LLMTR states data handling expectations on model pages and legal notices; applications should still minimize sensitive data before prompts are sent.

How to read cost control

LLM gateway cost is not just token price. Retry rate, long context, agent tool output, RAG context, and model switching strategy all affect total cost.

LLMTR shows model prices as catalog values and applies platform margin separately at credit top-up. That distinction keeps gateway cost separate from model unit price.

Frequently asked questions

Is every AI gateway also an LLM gateway?

No. Some AI gateway products cover many AI services; an LLM gateway specifically focuses on language-model calls, token usage, and model choice.

Which category does LLMTR fit?

LLMTR provides an OpenAI-compatible LLM gateway surface, while API keys, catalog, usage metering, and security controls also cover common AI gateway needs.

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