A gateway, and a routing decision you can read.
LiteLLM is a mature, open-source gateway. It gives you one interface to a hundred-plus providers, with load balancing, fallbacks, spend tracking and key management. It is a genuinely good piece of infrastructure and a lot of teams run it. OmnisRouter does a narrower thing well: it decides which model each request should go to, sends it to the cheapest model that can handle it, and returns a receipt for the choice. This page is about where they differ and where they fit together.
How they compare
| Dimension | LiteLLM | OmnisRouter |
|---|---|---|
| What it is | Open-source gateway and proxy | Open-core routing proxy |
| Providers | Broad, a hundred-plus | The pool you configure, fewer today |
| Routing basis | Load balancing and fallback across your deployments (latency, usage, cost) | Reads the prompt: cheapest model that clears the quality bar for its intent |
| Per-request receipt | Logs and spend tracking | Chosen model, confidence, alternatives, estimated saving, on every response |
| Decide without calling a model | No | Yes: POST /v1/route |
| Gateway features (virtual keys, budgets, guardrails) | Extensive | Minimal: BYOK, tokens, decision log |
| Client formats | OpenAI-compatible interface | Anthropic, OpenAI and Gemini in, returned in the client's own format |
| Routing model | Config strategies | Open, reproducible from public data, measured by OmnisBench |
| Licence | MIT (open source) | Apache-2.0 (open core) |
What LiteLLM is good at
LiteLLM is the broader, more mature tool, and it is not close. It talks to far more providers, it has a full proxy with virtual keys, budgets, rate limits, spend reporting, caching and guardrails, and it has a large community. If what you need is a solid gateway in front of many models with real operational controls, reach for LiteLLM. OmnisRouter is not trying to replace that layer.
Routing by task difficulty, with a receipt
The routing in a gateway is usually about spreading load and handling failure across the deployments you list. That is useful, but it does not look at the request and ask whether the task is easy enough for a small model. OmnisRouter does exactly that. It embeds the prompt in-process, matches it to an intent cluster, and picks the cheapest model whose measured quality clears the bar for that intent, escalating to a strong model when it is not sure. Then it shows its working: the chosen model, the confidence, the alternatives it ranked, and the estimated saving, on every response and in a cost-free preview endpoint. The model that makes those calls is open and rebuildable, and its coding and maths policy comes from real measurements, not a guess.
They can sit together
Both speak the OpenAI wire format, so they compose. If you already run a LiteLLM gateway for breadth and spend controls, you can put OmnisRouter's routing decision in front of it and keep the receipt. Use LiteLLM for the plumbing, OmnisRouter for the choice of where each request goes and the record of why.
Pick based on the job
LiteLLM
You want a broad, battle-tested gateway: many providers, virtual keys, budgets, spend tracking and guardrails.
OmnisRouter
You want a transparent cheapest-capable routing decision, with a receipt on every request and an open, reproducible model behind it.
See a routing decision, no spend
Run one process, add a key, and ask /v1/route what it would do before any request goes out.