Comparisons7 min read
OpenRouter vs LiteLLM
OpenRouter and LiteLLMare the two most common first answers to "we need one endpoint in front of many models." They solve that problem in opposite ways, and the choice usually comes down to a single question: who do you want operating the proxy?
The core difference
| OpenRouter | LiteLLM | |
|---|---|---|
| Hosting | Fully managed SaaS | You self-host |
| License | Proprietary service | MIT open source |
| Setup time | Minutes | Hours to days |
| Model access | 200+ via one key | 100+ via your own keys |
| Billing | Credits through OpenRouter | Direct to each provider |
| Ops burden | None | Yours — uptime, scaling, upgrades |
| Data path | Through OpenRouter | Stays in your infrastructure |
Where OpenRouter wins
- Speed to first request. One signup, one key, done. Nothing to deploy.
- Model breadth. New models often appear there before anywhere else, including ones you have no direct account for.
- Consolidated billing. One invoice instead of six provider accounts, which matters more than it sounds when procurement is involved.
Where LiteLLM wins
- Data control. Prompts never traverse a third-party service. For regulated workloads this is frequently non-negotiable.
- Your existing contracts. Keep negotiated provider rates, committed spend discounts, and enterprise agreements.
- Extensibility. It is your process — add custom callbacks, logging, and auth however you like.
The known tradeoff: at high concurrency (roughly 500+ RPS) LiteLLM's Python proxy layer adds meaningful latency. If you are at that scale and latency-sensitive, budget for tuning or look at a compiled gateway.
What neither one does
Both give you access to many models. Neither decides which model a given request should use. You still hardcode a model name, or hand-roll fallback logic, and every request pays premium-model prices whether it needed to or not.
That is the gap routing fills: score the candidates per request against cost, quality, and latency targets, then dispatch. See what LLM routing is and how it reduces API costs.