PrivateMind
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Models

Browse the models your org has access to and check capabilities before calling them.

The catalogue changes per environment and per org. Call GET /v1/models to see what's available. Don't assume a model exists or supports a given feature.

Loading model catalog...

List models

cURL 
curl -s "https://api.privatemind.com/v1/models" \
  -H "Authorization: Bearer $PMIND_KEY"

Returns an OpenAI-shaped response. Each model carries a model_type, a structured capabilities block, the derived supported_parameters list, and any role aliases:

JSON 
{
  "object": "list",
  "data": [
    {
      "id": "deepseek-v4-pro",
      "object": "model",
      "owned_by": "privatemind",
      "context_length": 131072,
      "model_type": "chat",
      "capabilities": {
        "tools": true,
        "response_format": true,
        "reasoning_effort": true
      },
      "supported_parameters": [
        "max_tokens", "temperature", "top_p", "top_k", "seed",
        "frequency_penalty", "presence_penalty", "stream", "stop",
        "reasoning", "include_reasoning",
        "tools", "tool_choice", "response_format", "reasoning_effort"
      ],
      "aliases": ["reasoning"]
    }
  ]
}

Capability discovery

Feature-detect against capabilities and supported_parameters, not the model id.

capabilities

Structured boolean flags. Only the capabilities a model has are present (an absent flag means false):

Flag Meaning
tools Accepts tools / tool_choice for function calling. See Tool use
response_format Accepts response_format for JSON mode / structured outputs
reasoning_effort Supports the reasoning_effort parameter (hybrid and thinking-only models)
image_input Accepts images in chat messages. See Vision

supported_parameters

OpenRouter-style list derived from the model's capabilities plus its base sampling controls — a complete list of what the model accepts. Includes reasoning / include_reasoning when the model emits chain-of-thought (see Streaming → Reasoning output), and reasoning_effort, tools, response_format mirroring the flags above. An empty list means the model is not chat-shaped.

model_type

What kind of model it is, so you can route to the right endpoint without trial and error:

model_type Endpoint
chat, vision-chat /v1/chat/completions (vision-chat also accepts image input)
embeddings /v1/embeddings
ocr, ocr-vision /v1/chat/completions (document extraction)
tts /v1/audio/speech
asr /v1/audio/transcriptions

The Hybrid badge in the table above flags models that can run in either thinking or non-thinking mode on a per-request basis. Toggle the mode with the reasoning_effort field on /v1/chat/completions: "off" disables thinking, "low"/"medium"/"high" enables it at increasing budgets.

Context length

context_length is the maximum total token window (prompt + completion). Set max_tokens to fit inside this limit. Exceeding the window returns a 400.

What the list contains

Sourced from the running PrivateMind deployment and filtered by:

  • What's actually live in this environment
  • What your org is permitted to use

The list you see is exactly the list of model ids you can call.

Where next

  • Chat completions for the request shape that consumes model ids.
  • Tool use and Vision for the capabilities you'll feature-detect against.
  • Errors for what happens when a model is unavailable or out of budget.