RouterOne vs LiteLLM
RouterOne vs LiteLLM: no servers to run, one account for every model
LiteLLM is an MIT-licensed, self-hosted proxy: you deploy and operate it yourself and open accounts, configure keys and settle billing with each upstream provider separately, while data stays entirely in your own infrastructure. RouterOne is a hosted LLM API gateway: sign up and start, with one account and one balance for every model, no inference markup and low-cost channels far below official pricing and discounted official channels, plus native support for the Gemini protocol and Alibaba Cloud Model Studio, Volcengine Seedance, MiniMax and xAI image and video protocols, and enterprise-grade organization management.
Last verified 2026-10-19
- Servers to run
- 0
- LiteLLM needs PostgreSQL in production, and Redis for multiple instances
- For every model
- 1 account
- LiteLLM needs a separate account and key for each upstream provider
- Native video vendor protocols
- 4
- Model Studio, Seedance, MiniMax and xAI — existing code only changes the base URL
RouterOne vs LiteLLM, feature by feature
| Feature | RouterOne | LiteLLM |
|---|---|---|
| Deployment | Hosted — sign up and start, nothing to deploy or operate | Open source, self-hosted: PostgreSQL in production, Redis for multiple instances; the official docs describe self-hosted deployment |
| Upstream accounts and billing | One account and one balance for every model, with unified billing and invoices | You configure an API key for each upstream provider and settle billing with each one |
| Model pricing | No inference markup; low-cost channels go far below official pricing, and stable official channels are discounted too | The software is free; models are paid at each upstream’s official price |
| Text protocols | Native OpenAI Chat, OpenAI Responses, Anthropic Messages and Gemini (generateContent), with most models callable across protocols | OpenAI Chat, Responses, Anthropic Messages and Gemini generateContent |
| Image and video | Image: OpenAI Images and Alibaba Cloud Model Studio. Video: native Model Studio, Volcengine Seedance, MiniMax and xAI request formats plus a unified task API — existing client code only needs a new base URL and key | Unified-format image generation, image editing and video APIs |
| Embeddings and audio | Embeddings, speech and rerank endpointsComing soon | Embeddings, speech, realtime, rerank, batches, fine-tuning and more |
| Multi-provider failover | 0 models are already served by multiple providers, with automatic failover and failed attempts not billed | Several routing strategies, fallbacks, retries and cooldowns — you connect and configure the upstreams yourself |
| Teams and budgets | Enterprise-grade organization management: organizations, workspaces and roles (including a finance role); spend limits per workspace, member and key | Budgets per key, team and user (database required); per-model budgets are an enterprise feature |
| Data control | Request and response bodies of successful text calls are not stored; customer content is never used for training | Self-hosted, so data stays in your infrastructure; no telemetry when self-hosted |
| Usage and export | Itemized charges for every call; monthly statements exported to Excel by key, model and workspace | Per-request cost in a response header; global spend reports are an enterprise feature |
| SSO and audit | SAML single sign-on and audit recordsComing soon | SSO, audit logs and RBAC are enterprise features, priced by deployment size |
Which one to choose
Choose RouterOne if
- You would rather not deploy and maintain a proxy, database and cache, and want to start calling models right after signing up
- You do not want to open accounts, manage keys and top up with each upstream provider, and want unified billing and invoices
- You want leading models far below official pricing through low-cost channels, or at a discount through stable official channels, with automatic failover across providers
- You want to call image and video models in the native Alibaba Cloud, Volcengine, MiniMax or xAI request formats
Choose LiteLLM if
- Data must stay in your own infrastructure, or you need an air-gapped or private deployment
- You already have cloud contracts or credits and want one call format on top of them
- You need a broader API surface such as embeddings, speech, batches and fine-tuning (embeddings and speech are on the RouterOne roadmap)
- You want to build on MIT-licensed code or deeply customize routing
Switch from LiteLLM to RouterOne
Both work with the OpenAI and Anthropic SDKs. Switching only changes the endpoint, key and model names — your application code stays as it is, and there is no proxy left to maintain.
- 1Sign up for RouterOne and create an API key in the console.
- 2Replace the base URL of your self-hosted proxy with the RouterOne endpoint, and the key with your new API key.
- 3Replace the custom model names from your proxy config with RouterOne manufacturer/model IDs, copied from the model page.
- Fallbacks and load balancing configured in your proxy are handled by automatic multi-provider failover in RouterOne; you can also set a routing strategy on the API key.
- Claude Code and the Anthropic SDK use the endpoint without /v1; the Gemini SDK can call generateContent directly.
import os
from openai import OpenAI
client = OpenAI(
base_url="http://0.0.0.0:4000",
base_url="https://gateway.routerone.ai/v1",
api_key=os.environ["LITELLM_KEY"],
api_key=os.environ["ROUTERONE_API_KEY"],
)
response = client.chat.completions.create(
model="anthropic/claude-sonnet-5",
messages=[{"role": "user", "content": "Hello"}],
)Frequently asked questions
Get started
Minutes from now,
your first request is live.
- 1Create an account
- 2Create an API key
- 3Swap the base_url and call
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LiteLLM and other product names mentioned on this page are trademarks of their respective owners. Information about third-party products is compiled from their official public sources for evaluation purposes only and may change; refer to each vendor's website for current details. To report an inaccuracy, contact support@amux.ai.