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    deepseek-ai/deepseek-v4-pro

    API Reference

    Deploy

    Ready to scale? Choose your deployment path.
    Deploying your application in production? Get started with a 90-day evaluation of NVIDIA AI Enterprise

    Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.

    Step 1
    Generate API Key

    Step 2
    Pull and Run the NIM

    $ docker login nvcr.io
    Username: $oauthtoken
    Password: <PASTE_API_KEY_HERE>
    

    Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.

    export NGC_API_KEY=<PASTE_API_KEY_HERE>
    export LOCAL_NIM_CACHE=~/.cache/nim
    mkdir -p "$LOCAL_NIM_CACHE"
    chmod -R a+w "$LOCAL_NIM_CACHE"
    docker run -it --rm \
        --gpus all \
        --shm-size=16GB \
        -e NGC_API_KEY \
        -v "$LOCAL_NIM_CACHE:/opt/nim/.cache" \
        -p 8000:8000 \
        nvcr.io/nim/deepseek-ai/deepseek-v4-pro:latest
    

    Step 3
    Test the NIM

    You can now make a local API call using this curl command:

    curl -X 'POST' \
    'http://0.0.0.0:8000/v1/chat/completions' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{
        "model": "deepseek-ai/deepseek-v4-pro",
        "messages": [{"role":"user", "content":"Which number is larger, 9.11 or 9.8?"}],
        "max_tokens": 64
    }'
    

    For more details on getting started with this NIM, visit the NVIDIA NIM Docs.

    Specifications

    DeepSeek V4 scales to 1M-token context windows with efficient MoE architecture for coding tasks.

    • Moe
    • agentic
    • coding
    • reasoning
    Provider
    DeepSeek AI
    Last Modified
    4 months ago
    Context Length
    1M
    Parameters
    2T
    Input Modalities
    Text
    Output Modalities
    Text

    Model Availability

    Free Endpoint
    Deprecated
    Partner Endpoint
    Available
    Download Available
    Available
    API calls in last 30 days
    7M