Comparison
Conifer and Helicone compared
Both give one API for AI models from many providers. This page sets out how each one works, using each company’s own published documentation.
Summary
Helicone is an observability platform with an AI gateway. It logs requests for analysis, offers sessions, prompts, datasets and alerts, and can be self-hosted from open-source code. Conifer is a hosted gateway that serves a named model only as named, reports the exact cost of every request, and refuses a request over a cost ceiling before any provider is called.
In March 2026 Mintlify announced that it was acquiring Helicone and that Helicone would continue in maintenance mode, with security updates, bug fixes and new models. Helicone’s site now says Helicone is no longer part of Mintlify, with details to come. Helicone details were read from helicone.ai, its documentation and Mintlify’s announcement on 7 November 2026. Plans and prices change; check the linked pages before you decide.
Side by side
| Topic | Conifer | Helicone |
|---|---|---|
| Main purpose | A gateway: model access, provider failover, a cost receipt on every response, spending limits and an optional router | Observability with a gateway: request logs, sessions, user analytics, prompts, datasets, alerts and a query language |
| Where it runs | A hosted service at one Conifer address; there is nothing to deploy | Helicone’s cloud, in a US or EU region, or self-hosted with Docker Compose, Kubernetes or a manual install. Enterprise lists on-prem deployment |
| Open source | The Conifer SDK for TypeScript and Python is open source; the gateway is a hosted service | Open source under the Apache 2.0 licence |
| 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 | A unified API for “100+ LLM providers”, paid with Helicone credits or with your own provider keys, which the provider bills directly |
| Interfaces | OpenAI Chat Completions, OpenAI Responses and Anthropic Messages, on one key | The OpenAI SDK format for every provider, and the OpenAI Responses format for OpenAI and Anthropic models |
| 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 | Credits at “0% markup”. Plans: Hobby is free with 10,000 requests; Pro is $79 a month; Team is $799 a month; Enterprise is custom; usage-based pricing applies above the included amounts |
| Choice of provider | The best available provider for the model. On a failure, the same model from another provider at the catalog price | The cheapest provider offering the model, with equal-cost providers load-balanced and the next provider tried on errors. A list in the model field can set the order yourself |
| A named model | Served as named, or refused. Other models are tried only if you list up to three fallbacks yourself | Automatic fallbacks are listed on every plan |
| Cost on each request | Every response carries the amount charged, itemised by token type, and a streamed response ends with the same receipt | Usage, cost and performance across providers in one dashboard |
| 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 | Custom rate limits by request count, cost or custom properties, set with a request header |
| Request logs | 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 | Requests are logged for analysis. Logs are kept 7 days on Hobby, 1 month on Pro, 3 months on Team and with no end date on Enterprise |
| Caching | On Anthropic models the gateway manages the provider’s prompt cache, so a long system prompt is paid for once and read at a lower rate after that | Complete responses cached on Cloudflare’s edge network, and prompt caching on providers |
| Enterprise terms | Team accounts with owner, admin and member roles, per-key model scope and spend caps, set up on request | Team adds SOC 2 and HIPAA compliance; Enterprise lists SAML SSO, a custom MSA and on-prem deployment |
Which one fits
- Helicone may suit you if
- Your main need is analysing LLM traffic, with sessions, users, prompts, datasets and your own queries; you want to self-host from open-source code; or you need data kept in an EU region.
- Conifer may suit you if
- You want a gateway that serves a named model only as named and states the model and the exact amount charged on every response, you want a cost ceiling enforced on each request before any provider is called, or you want automatic model choice limited to models you approve.
Moving from Helicone to Conifer
- Address and key
- Point your OpenAI client at Conifer 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. - Provider order
- Conifer picks the provider for each request and tries another provider for the same model if one fails. To try other models, list up to three fallbacks in a request header.
- Limits
- Set a cost ceiling on each request, and a spend cap on each key in place of per-user limits. Team accounts give each person their own key on one bill.
- Logs and analytics
- The Conifer console shows requests and cost for each key. If you rely on Helicone’s session, user or prompt analytics, plan where that work will live.
Replace your provider key has the full steps, Billing and caching covers ceilings and caps, and Teams covers team keys.
Read more
- 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 LiteLLM
- 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 Helicone?
- For the gateway, yes. Both give one API for models from many providers, with provider failover and cost records. Helicone is also an observability platform with sessions, prompts, datasets and alerts, and can be self-hosted. Conifer is a hosted gateway built around model access, cost receipts and spending limits.
- What is Helicone’s status after Mintlify?
- Mintlify announced in March 2026 that it was acquiring Helicone and that Helicone would continue in maintenance mode. Helicone’s site now says Helicone is no longer part of Mintlify, with details to come. Check helicone.ai for the current position.
- Do I need provider accounts to use Conifer?
- No. One Conifer key covers every model in the catalog, paid from a prepaid balance. You can also put your own Azure OpenAI resource behind the same key, and Conifer adds no fee on that usage.
- How does Conifer report cost?
- Every response carries the amount charged for the request, broken down into input, output and cached tokens, and a streamed response ends with the same receipt. The console shows requests and cost for each key.