Models and compatibility

Model IDs

Call GET /v1/models using the same key you will use for inference. Copy an exact data[].id into the request's model field. Do not substitute a dashboard display name or assume another provider's model ID exists on Netra.

Netra offers DeepSeek V4.1 Flash (deepseek/deepseek-v4.1-flash) and DeepSeek V4 Flash 0731 (deepseek/deepseek-v4-flash-0731). Each model has a separate card, Playground option, and token usage and billing history. The dashboard reads availability and pricing from the active public catalog.

OpenAI compatibility describes the supported HTTP formats. It does not imply support for every OpenAI endpoint, model, multimodal feature, or SDK helper. Image generation, audio, file upload, and fine-tuning endpoints are not supported. The Responses API supports the stateless operations described in its dedicated guide.

Context windows, generation limits, supported tools, JSON output, reasoning fields, and sampling options vary by model. Unsupported features can return a validation error. Start with model, text messages, and a small generation limit, then add only the capabilities supported by the selected model.

Automatic tool choice (tool_choice: "auto"), forced tool calls, tool-result continuation, and strict JSON schema output are supported for DeepSeek V4 Flash 0731 through Chat Completions. Each API guide describes its own supported fields.

Set reasoning: {"enabled": false} explicitly when you want non-thinking Chat Completions. Start with small generation limits and keep requests within the model's context and body limits.

V4.1 Flash images and thinking

DeepSeek V4.1 Flash accepts text and images and returns text. You can use thinking with image input. V4 Flash 0731 remains text-only.

In Playground, choose DeepSeek V4.1 Flash, click Add images or paste an image, and send your question. PNG, JPEG and WebP are supported, with up to four images per message and 2 MB per image. You can preview and remove attachments before sending. A new chat and its images stay in memory until you choose Save conversation; saved images are available when you reopen the chat. Start a new chat if its accumulated images exceed the Playground request limit.

Playground starts with Thinking enabled, at low effort. Settings offer low, high and max, and allow thinking to be turned off. Existing conversations retain their saved setting. For API calls, explicitly send reasoning: {"effort":"high"} to enable thinking; image input uses OpenAI-compatible content parts:

{
  "model": "deepseek/deepseek-v4.1-flash",
  "messages": [{
    "role": "user",
    "content": [
      {"type": "text", "text": "Read the text and explain this image."},
      {"type": "image_url", "image_url": {"url": "data:image/png;base64,<BASE64_IMAGE>"}}
    ]
  }],
  "reasoning": {"effort": "high"},
  "max_tokens": 2048,
  "stream": true
}

Replace <BASE64_IMAGE> with the image bytes encoded as Base64. This is image input, not image generation or a file-upload endpoint. The API body limit is 64 MiB including image encoding and conversation history. Image tokens count toward prompt usage at the model's input rate; cached input uses the cached rate when reported. Reasoning tokens are part of completion usage, charged at the output rate. Do not add either token subset again.

Read delta.reasoning_content (or delta.reasoning) separately from delta.content when streaming. JSON responses use the corresponding fields under choices[0].message. See reasoning controls and SDK compatibility.

Prices and example cost

Published prices in USD per million tokens:

Verify current values in the dashboard catalog or deployed API reference. Organization-specific rates may apply. V4.1 Flash uses the same Chat Completions request format; set model to deepseek/deepseek-v4.1-flash. Public availability for each model is shown independently on Netra Status.

For V4 Flash 0731, a request with 1,200 prompt tokens (800 cached) and 300 output tokens costs (400 × 0.25 + 800 × 0.05 + 300 × 0.50) / 1,000,000 = $0.00029. For V4.1 Flash, the same usage costs (400 × 0.30 + 800 × 0.05 + 300 × 1.20) / 1,000,000 = $0.00052. Cached tokens are included in the 1,200 prompt tokens and must not be added again.

A model-list response identifies available IDs; its OpenAI-compatible shape is not a complete pricing or capability schema. Do not infer model-management or training API support from it.