Choosing a relay
How to choose an AI API relay
What an API relay actually is, how it differs from going direct or buying a subscription, and what to look at before you trust one.
A relay is an API gateway that sits between you and the model vendors: you send the request to it, it forwards to OpenAI, Anthropic or Google in each one's protocol, and hands the result back. From the calling side only two things change — the base URL and the key. The SDK, the request body and the response shape stay as they were.
People reach for one when three problems arrive together: payment and accounts (each vendor wants its own card, identity and balance), the network (a direct connection isn't reliable everywhere), and the per-vendor integration work (swapping models means another round of config). A relay collapses those into one URL and one key.
The cost deserves saying plainly: you've added a hop. Its uptime, its billing and its data handling all become things you carry too. Which is why choosing one is worth a few minutes — and the points below can all be checked before you pay.
What to look at
- 01
Are models listed by full identifier?
Models should be published as complete identifiers, version suffixes included, not as "the latest GPT". Tools match model names exactly, so vague naming means guessing every time you switch. Better still if /v1/models is implemented and you can fetch the list yourself — that endpoint is exactly what fills the model dropdown in Cherry Studio, Open WebUI and SillyTavern.
- 02
Are the protocol differences spelled out?
OpenAI-compatible, native Anthropic and native Gemini endpoints are not written the same way: some want /v1, some stop at the domain. Documentation worth the name states the form per tool instead of handing you one URL to experiment with. Getting that depth wrong shows up as a 404, and it accounts for a large share of failed setups.
- 03
How are limits and failed calls counted?
Concurrency ceilings, daily ceilings, and whether a failed request is still billed — all three are better read before paying than discovered at volume, because by then the cost of moving is yours.
- 04
Can you configure it inside the tools you already use?
A plain test: can Claude Code, Codex, Cursor and Cline each take a base URL and a key directly, or are you expected to move to the provider's own client? Anything that requires switching clients is really just locking you into its interface.
- 05
Is there someone to ask?
Setup problems are specific: where a given tool keeps its config file, what a particular error means. A channel you can actually ask in beats a frozen FAQ page.
- 06
Is the documentation written for a human?
How thorough the docs are is roughly the floor on support you'll get. Per-tool steps and the causes behind common errors mean somebody actually walked the path; "OpenAI-compatible" as the entire instruction means you'll be working it out alone.
Questions that keep coming up
How is a relay different from using the official API?
For your code, barely at all — same SDK, same request body. The difference is accounts and billing: going direct means settling with each vendor, so several models means several accounts, cards and configurations, while a relay covers several upstreams from one account at the price of an extra dependency. If you're building at scale on a single vendor, direct is more direct. If you move between models often and don't want an account per vendor, what a relay saves you is the repeated work.
Relay or subscription, for a coding assistant?
It depends on whether you work in your own tools. Subscriptions are usually tied to the vendor's client and sell you time; API billing sells you volume and plugs into anything that accepts a custom base URL. If you live in Claude Code, Codex or Cursor and want to pick the model yourself, the API route is the freer one.
Why can a relay undercut the vendor?
Mostly bulk purchasing and routing: upstream pricing is tiered by volume, so pooled usage lands below what an individual pays topping up alone, and a request can take whichever available route suits it. That logic has a floor, though — a price clearly below cost usually means the saving is coming from somewhere else, like a quietly downgraded model or oversold concurrency. While you're comparing prices, check that what answers is the model you asked for.
What about handing a relay your data?
Your request content passes through the middle layer, so how that layer handles data is something you should know. At minimum: is there a stated position on not retaining request content, and can you rotate or revoke keys yourself at any time. For anything sensitive, redact on your side first — relay or no relay.
How XylemNode answers these
Measuring ourselves against the list: models are published in the console as full identifiers, and /v1/models is implemented so clients can fetch them; the host is always api.xylemnode.com, with the path depending on protocol — /v1 for the OpenAI-compatible format, no /v1 for Claude Code and Gemini CLI on their native protocols — and every tool guide states which form to use. These docs cover 17 common tools, each with installation, configuration and the errors that tool actually produces. Plan prices and the credits each one includes are listed openly on the home page, and plans carry no daily ceiling. Top-ups land 1:1 in the same account as plan credits, all drawn down per real call. If something is unclear, the QQ group is the place to ask.