Here's something comparison pages rarely admit: these two products barely compete.
LiteLLM is an open-source proxy and Python SDK — 52k+ GitHub stars, 100+ providers, used in production at companies like Netflix (their site's claim, not ours). You deploy it, you point it at your provider keys, and you get one OpenAI-shaped interface to every model you care about, plus virtual keys, budgets, load balancing, fallbacks, and guardrails. It's genuinely good infrastructure. It also assumes something about you: that you want to choose models, and you're willing to operate a service to do it well.
TierUp assumes the opposite. You send requests to tier-1 through tier-4 (Speed, Balance, Intelligence, Reasoning) and we route each one to what we assess as the best-value model in that class right now. No model names — responses strip them out so your code can't grow a dependency on a checkpoint. No proxy to deploy. Also, candidly, no self-hosting option, no SSO, no admin dashboard for your team, and ~zero production users. We're a hosted abstraction in public beta, built on top of OpenRouter, and we say so on every page including this one.
So the real question isn't "which gateway is better." It's: do you want to own the model decision (and the box it runs on), or delegate both?
| TierUp | LiteLLM | |
|---|---|---|
| What it is | Hosted API with 4 performance tiers; we pick the model behind each tier | Open-source proxy server + Python SDK giving one interface to 100+ providers; you pick the models |
| Who picks the model | We do — tier mappings are versioned server-side, and responses strip provider/model details | You do. LiteLLM routes to whatever you configure, with fallbacks and load balancing you define |
| Where it runs | Our infrastructure (which routes via OpenRouter today) | Yours — your cluster, your Redis, your Postgres, your pager |
| Ops burden | None on your side beyond an API key | Real: deploy, upgrade, monitor, and scale the proxy yourself, or pay for their enterprise/cloud offering |
| Model churn | Ours. A better model ships, we re-map the tier, your code doesn't change | Yours. LiteLLM makes swapping models easy, but deciding when and what to swap to is still your job |
| Software cost | No platform fee; you pay per token | Free and open source; enterprise tier (SSO, audit logs, support) is custom-priced |
| Token cost | Flat per-tier, ~50% under the retail price of the underlying models (tier 2: $1.50/$7.50 per 1M in/out vs ~$3/$15 retail Sonnet-class). Transparently subsidized while we test product–market fit. Tier 1 currently free | Retail — you bring your own provider keys and pay each provider's list price |
| Spend controls | Prepaid wallet, per-request usage logging, daily spend guardrail | Virtual keys, per-key/team/org budgets, rate limits, cost tracking — considerably richer than ours |
| SDK compatibility | OpenAI-compatible: change the base URL, set model to a tier | OpenAI-compatible by design; also callable as a Python SDK |
| Maturity | Public beta, built solo, ~zero users. Not a typo | 52k+ stars, huge community, serious production adoption. On maturity, LiteLLM wins without breaking a sweat |
Use LiteLLM if:
Use TierUp if:
Use both, plausibly: LiteLLM proxies any OpenAI-compatible endpoint, and TierUp is one. Some teams will route most traffic through models they chose, and point one LiteLLM deployment at a tier for workloads where the class matters more than the name. We'd count that as a win, not a compromise.
LiteLLM's software is free; your costs are provider tokens at retail plus the infrastructure and engineering hours to run the proxy well. TierUp charges no platform fee and prices tiers ~50% below the retail cost of the models behind them — and we currently eat that difference, on purpose, capped by a daily spend guardrail, while we find out whether developers will hand model choice to a router. That subsidy is a funded experiment, not a business model. If we earn long-term margin, it comes from volume pricing and routing optimization. You should know that before you build on us, so: now you do.
No. TierUp is hosted-only, and the tier abstraction is the product — the server-side mapping of tiers to models is the part we operate for you. If your security posture requires the gateway inside your own network, LiteLLM is the right call and we won't argue.
The software is free; the tokens aren't. With LiteLLM you pay every provider's retail price plus whatever it costs you to run the proxy. TierUp's tiers are priced ~50% under retail because we subsidize them during product–market-fit testing — transparently, with a cap. Cheaper today, yes; permanent, we can't promise.
Mostly no. We have a prepaid wallet, per-request usage logging, and a daily spend guardrail. LiteLLM's access-control and budgeting machinery is far deeper. If you're provisioning an organization rather than an app, that gap probably decides it.
We don't say, deliberately — responses strip model and provider details so nothing in your stack can depend on a checkpoint. We commit to the class instead: tier 1 speed-class, tier 2 balance-class, tier 3 intelligence-class, tier 4 reasoning-class. If you need to know and pin the exact model, use LiteLLM (or a direct API); that need is exactly what TierUp is built to remove, so it's a poor fit for you by design.
Also see: TierUp vs OpenRouter · LLM API cost calculator
Try a tier before you believe any of this.
The playground at tierup.ai/try works without signing up — no proxy to deploy, no keys to bring. If you like it, signup gets you $25 in credit, no card required.