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Use case

Products that use more than one model

Products that mix models — a fast one for routine steps, a stronger one for hard tasks, another lab for a second opinion — tend to collect several accounts, keys, SDKs and invoices. BoostRail puts 59 text models from 11 labs behind one key, one balance and one bill.

Text models
59
Labs
11
Leading models
At or below official list price
Billing
One USD balance

What this workload needs

  • Switching or mixing models without a new integration each time.
  • One place to see spend per model, key and project.
  • Predictable behavior when a model's service has an incident.
  • Prices that can be checked against the labs' own lists.

How BoostRail handles it

  • One OpenAI-compatible endpoint; the model parameter picks the model, and GET /v1/models lists the ids your key can call.
  • Every model's per-token price is public, and leading models are priced at or below their official list prices.
  • Usage can be broken down by project, API key and model, and exported as CSV.
  • When a route fails, the request is retried on another route of the same model. It is never switched to a different model.
  • Request fields that are not applied are named in the x-boostrail-degraded response header instead of being dropped silently.

Set it up

  1. Point your OpenAI SDK at https://api.boostrail.com/v1 with a BoostRail key.
  2. Pick model ids from the Models page.
  3. Use separate keys per environment or feature to see spend split the way you need.

Limits to know

Current behavior, the same as in the Docs.

  • Chat Completions accepts n = 1 only.
  • audio, web_search_options and non-text modalities return 400 unsupported_parameter.
  • Non-streaming requests stop at 180 seconds; stream long generations.
  • Some models carry an input cap, marked on the Models page.

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59 text models from 11 labs behind one key, one balance and one bill.

Last updated: 2026-10-03