Documentation

AI infrastructure that works with the OpenAI API

Public Models

Public models are pre-deployed inference endpoints operated by QDivZero. You call them by name — no launch wizard, no GPU selection, no scheduler. Usage is measured from each inference request and evaluated against the published input and output rates. Under the hood, the platform routes the request across the providers that host each model.

Public models vs. Compute instances

A Compute instance is a model you deploy against a Hugging Face repo, billed per active GPU hour, with a serving name you pick. A public model is a model QDivZero deploys, with usage-based inference rates and a fixed name from the catalog. Use Compute for private or experimental models; use public models for production traffic against the most common frontier models without managing capacity.

Catalog

The current catalog. The platform adds models as providers expose them. Rates are expressed in EUR per one million input or output tokens as the standard unit for measuring inference usage.

ModelWorkloadEuropeanInput / MOutput / M
deepseek-v3.2chatNo€0.35€1.43
deepseek-v3.2-europeanchatYes€0.81€2.18
gpt-oss-120b-europeanchatYes€0.34€1.37
gpt-oss-safeguard-120b-europeanchatYes€0.34€1.37
gpt-oss-20b-europeanchatYes€0.09€0.39
gpt-oss-safeguard-20b-europeanchatYes€0.09€0.39

Variants ending in -european

European variants are pinned to a single EU region and stay inside the EU for data-residency. They are billed at a different rate than the global variant of the same model.

Where to go next

Calling public models →

curl and OpenAI SDK examples, plus which features are forwarded to the provider.

Pricing model →

How inference usage is measured, rated, and recorded in the ledger.

Use in Smart Balancers →

Reference a public model as a route destination or as the intent classifier.

Inference →

Full request shape: backend selection, firewall, tools, and streaming.