Custom Models

Upload your own Hugging Face weights and serve them through the same OpenAI-compatible API as the catalog. Fine-tunes and distilled open-weight models run on the same infrastructure, pinned versions, and audit trail as catalog models. vLLM/SGLang models work out of the box, and we stand up custom runtimes for models that need them.

Custom model hosting is arranged per customer as part of an enterprise agreement. Talk to us with the model and your expected volume.

Register a model

1. In the console, open Custom Models and choose Add model.
2. Enter the Hugging Face model id (for example your-org/your-finetune) and its architecture (the base family it derives from, e.g. Qwen or Llama).
3. If the repository is private, mark it as such so we can arrange access.
4. Submit. The model appears with status pending while we provision it, then flips to available.

Call your model

Once the model is available, use it exactly like a catalog model: same endpoints, same request shape, same pinned-version guarantees. Reference it by the model id you registered:

sference responses create \
  --model "your-org/your-finetune" \
  --content "Summarize this contract in three bullet points." \
  --wait

You can also open it in the playground from the console, or route production traffic to it through a dedicated deployment.

Billing

Hosting and per-token rates for custom models are agreed per customer as part of an enterprise agreement, not published as a rate card. Pricing depends on the model, the hardware it needs, and your volume. Every request carries the same request-level logging and audit trail as catalog traffic.

Next steps