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Method: client.get_models().

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Example

models = client.get_models({
    "provider": ["anthropic"],
    "provider_status": ["beta", "not_ready"],
    "provider_availability_reason": ["preview_only", "provider_not_ready"],
    "capability_status": ["coming_soon", "internal_testing"],
    "availability": "all",
})

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Parameters

  • Optional filters: provider, provider_status, provider_routing_status, model_routing_status, capability_status, provider_availability_status, provider_availability_reason, status, organisation, endpoints[], input_types[], output_types[], params[], availability, limit, offset.
  • provider_availability_reason is useful with availability="all" when you want rollout-state entries such as preview_only, provider_not_ready, gated, access_limited, region_limited, project_limited, paused, or soft_blocked.
  • capability_status is useful with availability="all" when you want non-routable endpoint mappings such as coming_soon or internal_testing.

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Returns

ModelListResponse 
{
  "ok": true,
  "limit": 50,
  "offset": 0,
  "total": 123,
  "models": [
    {
      "model_id": "openai/gpt-4o-mini",
      "name": "GPT-4o Mini",
      "release_date": "2024-07-18",
      "status": "active",
      "organisation_id": "openai",
      "aliases": ["gpt-4o-mini"],
      "endpoints": ["chat/completions", "responses"],
      "input_types": ["text"],
      "output_types": ["text"],
      "providers": [
        {
          "api_provider_id": "openai",
          "params": ["temperature", "max_tokens"]
        }
      ]
    }
  ]
}
Last modified on May 6, 2026