Is Conifer an alternative to LiteLLM?

Yes, if you would rather use a hosted gateway than run one. Both give one OpenAI-compatible API for models from many providers, with fallbacks, budgets and cost tracking. LiteLLM runs on your own infrastructure with your provider keys. Conifer is hosted and sells model usage from a prepaid balance.

Can I use LiteLLM and Conifer together?

Yes. LiteLLM can call any OpenAI-compatible endpoint, so you can add Conifer as a provider in a LiteLLM gateway and keep your keys, budgets and logs there.

Do I need to run anything to use Conifer?

No. Conifer is a hosted service. Create a key, set the base URL in your client, and send requests.

Does Conifer store my prompts?

The gateway does not store the prompt of a standard request. It holds a response for ten minutes so that a retried request is not charged twice, and keeps request details such as the model, token counts and cost for billing.

Comparison

Conifer and LiteLLM compared

Both give one OpenAI-compatible API for AI models from many providers. LiteLLM is a gateway you run yourself and Conifer is a hosted one. This page sets out how each works, using each company’s own published documentation.

Summary

LiteLLM is an open-source gateway and Python SDK. You run the gateway on your own infrastructure, in front of provider accounts you hold, and its Enterprise licence adds single sign-on, audit logs and support. Conifer is a hosted gateway. There is nothing to deploy, model usage is paid from a prepaid balance, and every response states the model that served it and the exact amount charged.

LiteLLM details were read from litellm.ai and docs.litellm.ai on 7 November 2026. Features and licence terms change; check the linked pages before you decide.

Side by side

Topic	Conifer	LiteLLM
Where it runs	A hosted service at one Conifer address; there is nothing to deploy	A server you run in your own environment with Docker, Helm or Terraform, alongside a Postgres database. Enterprise also lists air-gapped deployment
Who operates it	Conifer runs the service, chooses the provider for each request and retries another provider on failure	Your team. LiteLLM’s production checklist covers configuration, sizing and workers, Redis, and the database and its migrations
Licence	The Conifer SDK for TypeScript and Python is open source; the gateway is a hosted service	Open source under MIT. Enterprise features are switched on by a licence key on the same gateway image
Model access	More than 230 models paid from one prepaid balance, with no provider accounts needed; your own Azure OpenAI resource can sit behind the same key	You add the models and provider keys you hold, including internal, fine-tuned and self-hosted models. LiteLLM describes one API to “140+ providers and 1,800+ models”
Interfaces	OpenAI Chat Completions, OpenAI Responses and Anthropic Messages, on one key	The OpenAI format, plus endpoints in the shape of OpenAI Responses and Anthropic Messages
What you pay	Per-token prices published in the catalog, from a prepaid balance, with no subscription. No Conifer fee on usage of your own Azure resource	The open-source gateway is free, with “no markup on model spend”, and it runs on servers and a database you provide. Enterprise is priced on request, with a 30-day trial
A named model	Served as named, or refused. Other models are tried only if you list up to three fallbacks yourself	Fallbacks set in the gateway configuration move a call that still fails after its retries to another model group. Load balancing spreads traffic across deployments
Cost on each request	Every response carries the amount charged, itemised by token type, and a streamed response ends with the same receipt	Spend is tracked for each key, user, team and tag, calculated from LiteLLM’s model cost map, and the calculated cost is also returned in a response header
Spending limits	A cost ceiling per request, a spend cap per key and a monthly limit on the account. A request that could exceed a ceiling is refused before any provider is called	Budgets and rate limits for each key, user, team and customer
Data handling	Requests pass through Conifer and the provider that serves them. The prompt of a standard request is not stored, a response is held for ten minutes so a retry is not charged twice, and request details such as model, tokens and cost are kept for billing	Prompts, responses and provider keys stay in your infrastructure. Request and response content is not stored in its logs unless you turn that on
Enterprise terms	Team accounts with owner, admin and member roles, per-key model scope and spend caps, set up on request	SSO and SCIM (free for up to five users), audit logs, team admins, secret managers, multi-region and support SLAs with a one-hour target when all production traffic is failing; SOC 2 Type II; invoicing or AWS and Azure Marketplace

Which one fits

LiteLLM may suit you if: Requests and provider keys must stay inside your own infrastructure, you already hold provider contracts and want one gateway in front of them, you want internal or fine-tuned models behind the same key, or your team wants to run and change the gateway itself.
Conifer may suit you if: You would rather not run a gateway, its database and its upgrades; you want many models on one prepaid balance without an account with each provider; you need each response to state the model that served and the exact amount charged; or you want a cost ceiling enforced before any provider is called.
Using both: LiteLLM can call any OpenAI-compatible endpoint, so a LiteLLM gateway can list Conifer as one of its providers. Your keys, budgets and logs stay in LiteLLM, and Conifer serves the models.
model_list: - model_name: claude-opus-5 litellm_params: model: openai/claude-opus-5 api_base: https://api.conifer.build/v1 api_key: os.environ/CONIFER_API_KEY

Moving from LiteLLM to Conifer

Address and key: Point your OpenAI or Anthropic client at Conifer in place of your gateway, and use a Conifer key.
OPENAI_BASE_URL=https://api.conifer.build/v1 OPENAI_API_KEY=$CONIFER_API_KEY
Model names: Use the model names in the Conifer catalog. Names with the lab in front, such as anthropic/claude-opus-5, are also accepted.
Fallbacks: Conifer tries another provider for the same model on its own. To try other models, list up to three fallbacks in a request header.
Keys and budgets: Give each person or service its own key with a spend cap. Team accounts are set up by Conifer, and an admin can limit a key to a list of models.
Coding tools: Claude Code, Codex, Cursor, VS Code, Aider, Zed, opencode and Open WebUI each have a setup page under Tools.

Replace your provider key has the full steps, Any client covers other OpenAI-compatible software, and Teams covers team keys.

Conifer Gateway: One API key and endpoint for every model in the catalog, with the model and cost stated on every response.
What is an LLM gateway?: How a gateway sits between your software and the companies that serve models, and what to check when you choose one.
Conifer vs OpenRouter: The two gateways side by side, from each company's own documentation.
Conifer vs Portkey: The two gateways side by side, from each company's own documentation.
Conifer vs Helicone: The two gateways side by side, from each company's own documentation.
All comparisons: Conifer compared with eleven other LLM gateways and routers, from their own documentation.

Questions

Is Conifer an alternative to LiteLLM?: Yes, if you would rather use a hosted gateway than run one. Both give one OpenAI-compatible API for models from many providers, with fallbacks, budgets and cost tracking. LiteLLM runs on your own infrastructure with your provider keys. Conifer is hosted and sells model usage from a prepaid balance.
Can I use LiteLLM and Conifer together?: Yes. LiteLLM can call any OpenAI-compatible endpoint, so you can add Conifer as a provider in a LiteLLM gateway and keep your keys, budgets and logs there.
Do I need to run anything to use Conifer?: No. Conifer is a hosted service. Create a key, set the base URL in your client, and send requests.
Does Conifer store my prompts?: The gateway does not store the prompt of a standard request. It holds a response for ten minutes so that a retried request is not charged twice, and keeps request details such as the model, token counts and cost for billing.