A direct line to your model.

Ask a question, see the answer arrive token by token, and keep the full OpenAI-compatible request within reach when you want to go deeper.

Model economicsReseller estimate

Instance

€0.80 / hour

Cost / 1M

~€0.11

Aggregate

2,000 tok/s

Per user

>95 tok/s

Concurrency

+20 users

Output / hour

7.2M tok

Estimated equivalent at full aggregate utilization for 20 concurrent users. QDivZero bills the instance by the hour, not by token.

Open the demo

Separate, time-limited test experience. Availability is subject to change.

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QDivZero chat

nvidia/qwen3.6-35b-a3b-nvfp4-for-demo

Processed 0 / 128k tok

Enter to send · Shift+Enter for a new line

Test notice: messages and responses are logged for testing purposes but are not retained. Please do not include sensitive information.

Request JSONmodel, messages, stream and moreEdit

VS Code / Copilot

Bring QDivZero into Copilot.

Add the endpoint as a custom model in VS Code and use QDivZero from the Chat view. No API key is required for this demo.

  1. 01

    Open Manage Language Models

    In VS Code, open the Chat model picker and choose Add Models, then Custom Endpoint.

  2. 02

    Choose Chat Completions

    Use https://qdiv0.com/api/qdiv0/v1 and leave the API key as not-needed.

  3. 03

    Paste the model definition

    Save the generated chatLanguageModels.json and select the model in Chat.

chatLanguageModels.json
[
  {
    "name": "QDivZero",
    "vendor": "customendpoint",
    "apiKey": "not-needed",
    "apiType": "chat-completions",
    "models": [
      {
        "id": "nvidia/qwen3.6-35b-a3b-nvfp4-for-demo",
          "name": "Qwen 3.6 35B A3B NVFP4 for demo",
        "url": "https://qdiv0.com/api/qdiv0/v1",
        "toolCalling": true,
        "thinking": true,
        "streaming": true
      }
    ]
  }
]

Keep the API key in VS Code's secret storage. Tool calling requires a model and deployment that expose tool support.