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nvidia

cosmos-reason1-7b

Run Anywhere

Reasoning vision language model (VLM) for physical AI and robotics.

Physical AIautonomous vehiclesindustrialreasoningroboticssmart citiesSynthetic Data Generationvideo understandingvision language model
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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 "$LOCAL_NIM_CACHE"
docker run -it --rm \
    --gpus all \
    --ipc host \
    --shm-size=32GB \
    -e NGC_API_KEY \
    -v "$LOCAL_NIM_CACHE:/opt/nim/.cache" \
    -u $(id -u) \
    -p 8000:8000 \
    nvcr.io/nim/nvidia/cosmos-reason1-7b: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": "nvidia/cosmos-reason1-7b",
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": "What is in this video?"
                    },
                    {
                        "type": "video_url",
                        "video_url":
                            {
                                "url": "https://assets.ngc.nvidia.com/products/api-catalog/cosmos-reason1-7b/av_construction_stop_timestamped.mp4"
                            }
                    }
                ]
            }
        ],
        "max_tokens": 256
    }'

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