OpenRouter vs LiteLLM, and Where PromptUnit Fits

OpenRouter and LiteLLM are often compared because both sit between your application and the model providers. They do different jobs. OpenRouter is a hosted gateway: one key, one bill, hundreds of models. LiteLLM is an open-source gateway you run on your own servers. PromptUnit is a third kind of tool: a cost layer that decides, request by request, whether a cheaper model is just as good, and it can run on top of OpenRouter with your own OpenRouter key.

This guide explains what each one does, using each project's own documentation (checked October 2026), and how they fit together.

What Each Tool Actually Is

OpenRouter: one key for hundreds of models

OpenRouter is a hosted service with one API endpoint for hundreds of models from many providers. You get one account, one key and one bill instead of an account with every provider.

Pricing, from OpenRouter's FAQ: model prices are passed through from the providers without markup. OpenRouter charges a fee when you buy credits: 5.5% by card ($0.80 minimum) or 5% with crypto. If you bring your own provider keys, there is no fee for the first $25,000 of usage a month, then 5%.

OpenRouter also picks models for you if you ask it to. Its Auto Router is free: it sorts your prompt into one of about 30 task types and picks a model based on what OpenRouter users spend on for that task. You pay the standard rate of the model it picks. Business and Enterprise plans can keep requests inside the EU or the US with in-region routing, for the models that support it.

What OpenRouter does well:

One key and one bill for hundreds of models
Provider prices with no markup on the models
Fallbacks across providers for better uptime
A free Auto Router for teams that want OpenRouter to choose the model

What it is not built for:

Starting from the model your app asked for and switching only when a cheaper one is just as good for that request
Showing what each request saved compared with the model you asked for

LiteLLM: the open-source gateway you host

LiteLLM is an open-source Python library and proxy server. You run it yourself, and it gives your code one OpenAI-compatible API for 100+ providers. You pay the providers directly, with nothing added, and you run and maintain the servers.

LiteLLM has budgets and spend tracking per key, load balancing and fallbacks. It also has an auto router, in beta, that scores each prompt's complexity and sends it to the model you set for that tier (simple, medium, complex or reasoning). An Enterprise plan adds features like single sign-on and support; its price is on request.

What LiteLLM does well:

No markup: you pay providers directly
Full control: it runs on your own infrastructure
Budgets, spend tracking and load balancing per key
A large open-source community and many provider integrations

What it leaves to you:

Running, scaling and updating the servers
Choosing the models for each tier, and checking that the cheaper tier is good enough for your traffic
Reporting what you saved compared with the model you asked for

PromptUnit: the cost layer

PromptUnit is a hosted proxy focused on one thing: paying less for the same results. It starts from the model your app asked for. Each request is checked: when a cheaper model is just as good for that request, PromptUnit uses it, and when it isn't, the request goes to the model you asked for. A quality setting controls how careful the switching is, and the header x-promptunit-routing: off keeps any request on its model.

The dashboard shows every request from the first one: the model you asked for, the model that answered, what it cost and what it saved. Pricing: free until PromptUnit has saved you money, then 20% of what it saves. If it saves nothing, you pay nothing. Model prices are not marked up.

PromptUnit works with OpenAI, Anthropic, Google, Groq and DeepSeek keys, and with OpenRouter: connect your own OpenRouter key, point your app at PromptUnit's OpenRouter address (OpenAI or Anthropic format), and every call runs on your key and your OpenRouter credits. On OpenRouter, switching currently stays within the same model family, for example from a large Claude model to a cheaper Claude model.

What PromptUnit does well:

Switches only when a cheaper model is just as good for the request
Shows the saving on every request, starting with the first one
Pay-for-results pricing, with nothing added to model prices
Works with your direct provider keys or your OpenRouter key

What it does not do:

Self-hosting (it is a hosted service, running in the US)
Full tracing and observability like Langfuse or LangSmith
A published uptime SLA

Comparison Table

	OpenRouter	LiteLLM	PromptUnit
What it is	Hosted gateway to hundreds of models	Open-source gateway you host	Hosted cost layer
Models	Hundreds, behind one key	100+ providers, with your own keys	Major providers, or OpenRouter models through your OpenRouter key
Picks the model for you	Free Auto Router (by what users spend on per task type)	Auto router in beta (complexity tiers you set up)	Starts from your model, switches only when a cheaper one is just as good
Pricing	Provider prices, no markup; 5.5% fee on card credit purchases	Free open source; Enterprise on request	Free until it saves you money, then 20% of savings
Savings view	Spend per request	Spend per key and team	Saving per request, compared with the model you asked for
Data location	Global; EU or US in-region routing on Business and Enterprise plans	Your own infrastructure	US
Setup	Minutes	Hours to days	Minutes (one line)

Using Them Together

These tools stack more than they compete.

PromptUnit + OpenRouter. OpenRouter gives you access to the models and one bill. PromptUnit decides, for each request, whether a cheaper model is just as good, and shows the saving. You connect your own OpenRouter key; calls are paid from your OpenRouter account, and PromptUnit charges only its share of the savings.

LiteLLM + PromptUnit. LiteLLM can send requests to any OpenAI-compatible address, so a team that runs LiteLLM can also point a model at PromptUnit and keep LiteLLM for its budgets and keys.

Which one to start with:

OpenRouter if you want many models behind one key and one bill.
LiteLLM if you need to run everything on your own servers and have the team to do it.
PromptUnit if your problem is the size of the AI bill, and you want the savings checked per request, on OpenRouter or on your direct provider keys.

For context on what an inference proxy is at the infrastructure level, see What Is an AI Inference Proxy. For the LLM gateway concept and its full feature set, see What Is an LLM Gateway. For the cross-provider routing strategy that makes these savings possible, see Cross-Provider LLM Routing.

Try It Free

See exactly where your AI budget is going. PromptUnit shows every request with the model that answered, what it cost and what it saved, starting with your first one.

Start free. Or talk to us if you want a walkthrough.