ProxyLLM vs OpenRouter: Different Problems, Different Tools

We sell one of the two products on this page, so here is the version we would want to read. OpenRouter and ProxyLLM are not really competitors: OpenRouter sells model breadth, hundreds of models behind one per-token API. We sell a cost model, flat OpenAI volume by running Codex on your own ChatGPT subscription, plus a no-markup passthrough for your own keys. If your problem is “I need many models,” buy OpenRouter. If your problem is “my OpenAI bill scales with every call,” that is the problem we built for. Plenty of teams run both.

What OpenRouter is good at

OpenRouter earns its place. One API key reaches hundreds of models across OpenAI, Anthropic, Google, Meta, Mistral, and the open-weight world; switching models is a string change; provider outages can fail over to another host serving the same weights. Pricing is provider passthrough plus a fee, roughly 5% on credit purchases as of mid-2026, per OpenRouter’s published pricing. Responses stream. For multi-model products and fast experimentation, it is the obvious default, which is why it headlines our own survey of OpenRouter alternatives.

What OpenRouter does not change is the meter. Every token still bills per token, plus the fee. If 90% of your traffic is OpenAI models, OpenRouter gives you breadth you are not using and a meter you are trying to escape.

What ProxyLLM is good at

We do one structural thing: Codex Hosted runs OpenAI’s official, unmodified Codex CLI on managed servers, signed into your own ChatGPT account through OpenAI’s device-code flow. Your OpenAI-bound workloads bill to the flat subscription instead of the per-token meter. The fee is $129 a month with no inference markup; as planning estimates, a Plus plan absorbs roughly $700 of API-equivalent work monthly, Pro 5x roughly $3,500, Pro 20x roughly $14,000. Estimates, never guarantees, and programmatic Codex use is documented functionality with OpenAI holding the final call.

Around that lane: bring-your-own keys (OpenAI, OpenRouter) pass through with no markup, encrypted AES-256-GCM; when a plan window exhausts, requests fall back to a second connected account, then your API key; and the request log names the lane that served every call.

Side by side

Axis	OpenRouter	ProxyLLM
Built to solve	One API for hundreds of models	Flat-cost OpenAI volume
Cost model	Per token, provider rate plus ~5% fee	$129/mo + your ChatGPT plan, no inference markup
Model surface	Hundreds, multi-vendor	OpenAI via the Codex lane; anything via your own keys
Streaming	Yes	Key lanes stream; the Codex lane returns complete responses
Fallbacks	Across providers and hosts	Across lanes: second account, then your API key
Scales with usage	Bill grows per token	Flat until window limits, then metered overflow
Best for	Multi-model products, experimentation	OpenAI-heavy agents, batch jobs, pipelines above ~$150/mo

Running both together

The combination is straightforward because both ends speak the OpenAI API shape. Point your app at our endpoint, route OpenAI-bound bulk work through the flat Codex lane, and connect your OpenRouter key as a passthrough lane for everything else: anthropic/, google/, and the rest bill at provider rates through your own key, no markup, same request log. You keep OpenRouter’s breadth where breadth matters and stop metering the OpenAI volume that did not need it. How we compare against the self-hosted way to get similar routing is in ProxyLLM vs LiteLLM.

Who should not buy ProxyLLM

Honesty earns more than a funnel, so plainly:

• You spend under ~$150 a month on OpenAI. The $129 fee plus a plan costs more than your meter. Stay direct or on OpenRouter; our Starter tier is $0 if you want the logs and dashboard anyway.
• Your product is a token-streaming chat UI. The Codex lane returns complete responses. If perceived latency from streaming is your UX, keep that traffic on a metered key lane, ours or anyone’s.
• Compliance requires direct provider contracts. If you need a DPA and a bill directly from OpenAI for every request, buy from OpenAI directly.
• Your spend is mostly non-OpenAI models. Our flat lane will not help; OpenRouter or LiteLLM fits better.

The decision framework behind the first two bullets, utilization and burst shape included, is in per-token vs flat-rate LLM pricing.

The short version

OpenRouter is a marketplace; we are a cost structure. A $3,500 metered OpenAI month maps to about $229 all-in on the subscription-backed setup, as an estimate, and that arithmetic is the entire reason we exist. If your bill is OpenAI-shaped, the calculator runs your number in thirty seconds; if it is not, OpenRouter is right there and we just told you to use it.