Models

List what your key can call

curl https://api.stav.ai/v1/models \
  -H "Authorization: Bearer $STAV_API_KEY"

for m in client.models.list():
    print(m.id)

The list contains:

• auto first — the Smart Router, using your workspace's default Router
• every model your workspace may use and whose Inference Provider is currently available
• your workspace's Routers, as @workspace/router entries (owned_by: "stav")

It is "what this key can call now", not the whole catalogue. Requires inference:models.

Read one model

curl https://api.stav.ai/v1/models/anthropic/claude-sonnet-4-5 \
  -H "Authorization: Bearer $STAV_API_KEY"

{
  "id": "anthropic/claude-sonnet-4-5",
  "object": "model",
  "owned_by": "anthropic",
  "context_length": 200000,
  "max_completion_tokens": 64000,
  "top_provider": { "context_length": 200000, "max_completion_tokens": 64000 },
  "stav_category": "llm",
  "stav_context_window": 200000,
  "stav_supports_thinking": true,
  "stav_capabilities": {

The stav_* fields are extensions; the OpenAI SDK exposes them via model_extra.

context_length, max_completion_tokens and top_provider use OpenRouter's names, so code written for OpenRouter reads them unchanged.

Use them as a pre-flight check:

info = client.models.retrieve("anthropic/claude-sonnet-4-5")
caps = info.model_extra.get("stav_capabilities") or {}
if not caps.get("vision"):
    raise RuntimeError("this pipeline needs a vision model")

GET /v1/models/{id} takes anything you can send as model: the canonical creator/model id, a bare name with exactly one match (nb-whisper-large), or a Router (@your-workspace/router). The answer always carries the canonical id. A pinned endpoint (creator/model/provider) is not a model: find it on the model's /endpoints.

See every Provider Endpoint

Different Inference Providers serve the same model with different limits and precision. List them:

curl https://api.stav.ai/v1/models/openai/gpt-oss-120b/endpoints \
  -H "Authorization: Bearer $STAV_API_KEY"

{
  "data": {
    "id": "openai/gpt-oss-120b",
    "name": "gpt-oss-120b",
    "endpoints": [
      {
        "id": "openai/gpt-oss-120b/groq",
        "provider_name": "Groq",
        "tag": "groq",
        "context_length": 131072,
        "max_completion_tokens": 65536,
        "quantization": null,
        "pricing": { "currency": "EUR",

• The numbers in this example are illustrative. Call the endpoint for current values.
• The list holds only the endpoints your key can reach. Your workspace's policy applies: sovereignty floor, compute region, ZDR, blocked providers.
• The order is the order Stav tries them in.
• Send an entry's id as model to pin that endpoint.
• pricing is what a request on that endpoint is charged, per token, in your workspace's currency. It is the same price billing uses. stav_conditional_rates: true means the endpoint also has prices that depend on the request, such as long context.
• The shape matches OpenRouter's /api/v1/models/{author}/{slug}/endpoints.
• A Router works here too, and so does auto: GET /v1/models/@your-workspace/router/endpoints lists every endpoint of every model the Router can pick, under the Router's own rules (ZDR, region, floor) as well as your workspace's, best model first. Each entry's model_id names its model, and data.stav_router is true. The models come 100 to a page: ?page=2, and data.stav_total_models is the whole pool.

Model ids

creator/model

The canonical form. Copy it from /v1/models or the catalogue. When a model has more than one Provider Endpoint, Stav chooses among those your workspace's policy allows.

creator/model/provider

Pins one Provider Endpoint. A pin narrows the choice; it never overrides your workspace's policy.

• No endpoint with that slug → endpoint_not_found
• The endpoint exists but your policy excludes it (or it is not live) → endpoint_not_admissible

Some endpoints carry a serving variant after a colon, e.g. zai-org/glm-5-2/fireworks-ai:fast. The variant only applies to a pinned endpoint.

Bare names and aliases

A name without a slash is resolved in order:

1. a registered alias — old slugs from before the creator/model rename, and ids the Inference Provider itself uses
2. the one active model whose id ends in /<name>

If two models share that last segment, the bare name matches nothing. Use creator/model in code you keep.

Unknown model

{
  "error": {
    "message": "The model 'openai/gpt-4o-turbo' does not exist or you do not have access to it.",
    "type": "invalid_request_error",
    "param": "model",
    "code": "model_not_found"
  }
}

The message covers both cases on purpose: Stav does not confirm that a model you cannot use exists.

Browse the full catalogue

The public catalogue needs no key:

curl "https://api.stav.ai/v1/public/models?page_size=20"
curl "https://api.stav.ai/v1/public/providers"

In Your workspace, Connect → Models and Connect → Inference Providers show the same catalogue with pricing, sovereignty and endpoints. Use /v1/models for "what can this key call"; use the catalogue for everything else.

Filter by type

Every model has a type — the door it is served on: chat, embedding or transcription. The catalogue opens on Chat; pass category= to switch, and filter on the type's own facts with capability=:

# embedding models with at least 1024 dimensions that support Norwegian
curl "https://api.stav.ai/v1/public/models?category=embedding&capability=embedding_dimensions:>=1024,languages:no"

# transcription models with word timestamps, priced at or under €0.01 per audio minute
curl "https://api.stav.ai/v1/public/models?category=transcription&capability=stt_timestamps_word&max_price=0.01&price_unit=audio_minutes"

A capability term is a slug (vision_input), slug:>=N for a number, or slug:code for a list; an unknown slug, or a value the fact does not take, is refused by name (422). Each item carries price_from and price_unit in the type's own unit (tokens_in, request or audio_minutes), and type_counts says how many models of each type match the other filters. GET /v1/public/model-types lists the types with their filters, units and benchmark sets.

Pin or route?

• Pin a model when you reproduce an evaluation or a contract names the model.
• Pin an endpoint when you need one Inference Provider specifically.
• Use a Router for most production traffic: failover, cost and latency trade-offs, and a sovereignty floor set once for the workspace. Change the Router, not your code.

Next

• Smart Router
• Request parameters
• Sovereignty