OpenClaw v2026.4.29 introduces NVIDIA as a first-class provider, giving you native access to Nemotron, Kimi, MiniMax, GLM, and other models from NVIDIA’s inference catalog. This guide walks you through getting those models working in your OpenClaw agent setup.

Prerequisites

  • OpenClaw v2026.4.29 or later (update via your standard update channel)
  • An NVIDIA NGC API key (free tier available at build.nvidia.com)
  • OpenClaw running in a configuration where you can edit provider settings

Step 1: Update to v2026.4.29

If you haven’t already, pull the latest OpenClaw version:

# Check your current version
openclaw --version

# Update (method depends on your install)
npm update -g openclaw
# or
openclaw update

Confirm you’re on 2026.4.29 or later before proceeding.

Step 2: Get Your NVIDIA API Key

  1. Go to build.nvidia.com and sign in or create an account
  2. Navigate to API Keys in your account settings
  3. Create a new key — name it something descriptive like openclaw-nvidia
  4. Copy the key; you’ll need it in the next step

NVIDIA’s free tier includes generous API credits for testing. Production usage will vary depending on your model selection and volume.

Step 3: Add the NVIDIA Provider in OpenClaw

Open your OpenClaw configuration:

openclaw config providers

This opens the provider management interface. Select Add Provider and choose NVIDIA from the provider catalog. You’ll be prompted for:

  • API Key: Paste your NVIDIA NGC key
  • Base URL: Leave as default (https://integrate.api.nvidia.com/v1) unless you’re using a self-hosted NIM endpoint
  • Default Model: Choose your preferred default from the catalog

Alternatively, edit your config file directly:

providers:
  nvidia:
    apiKey: "nvapi-YOUR_KEY_HERE"
    baseUrl: "https://integrate.api.nvidia.com/v1"
    defaultModel: "nvidia/llama-3.1-nemotron-70b-instruct"

Step 4: Explore the Model Catalog

The NVIDIA provider in OpenClaw ships with a model catalog you can browse:

openclaw models list --provider nvidia

Key models available at launch:

Model Best For
nvidia/llama-3.1-nemotron-70b-instruct General reasoning, instruction following
nvidia/llama-3.1-nemotron-nano-8b-instruct Fast, lightweight tasks
moonshot-ai/kimi-k1-5 Long-context reasoning
minimax/minimax-text-01 Multilingual, balanced quality
thudm/glm-4-9b-chat Chinese-language tasks, academic reasoning

Step 5: Test the Connection

Run a quick sanity check:

openclaw chat --provider nvidia --model nvidia/llama-3.1-nemotron-70b-instruct \
  "Hello, which model are you?"

You should get a response from the Nemotron model within a few seconds. If you get an auth error, double-check your API key has been saved correctly.

Step 6: Set NVIDIA as a Fallback or Routing Target

One of the most powerful uses of a multi-provider setup is intelligent routing. Configure your agent to fall back to NVIDIA when your primary provider is unavailable or rate-limited:

routing:
  primary: anthropic/claude-sonnet-4-6
  fallback:
    - nvidia/llama-3.1-nemotron-70b-instruct
    - openai/gpt-4o

Or use NVIDIA for specific task types (e.g., long-context document processing with Kimi):

routing:
  rules:
    - condition: "context_length > 100000"
      model: "moonshot-ai/kimi-k1-5"
      provider: nvidia

Step 7: Configure for Self-Hosted NIM (Optional)

If your enterprise runs NVIDIA NIM microservices on-premises for data sovereignty or latency reasons, point OpenClaw at your internal endpoint:

providers:
  nvidia:
    apiKey: "nvapi-YOUR_LOCAL_KEY"
    baseUrl: "https://your-nim-host.internal/v1"
    defaultModel: "nvidia/llama-3.1-nemotron-70b-instruct"

This works identically to the cloud endpoint — NVIDIA NIM uses the same OpenAI-compatible API format that OpenClaw natively supports.

Troubleshooting

“Provider not found” error: Make sure you’re on v2026.4.29 or later. Earlier versions don’t have the NVIDIA provider built in.

Auth failures: NVIDIA NGC keys are prefixed nvapi-. If yours doesn’t start that way, you may have copied the wrong token from the dashboard.

Model not in catalog: NVIDIA’s available models change as new ones are added to NIM. Run openclaw models list --provider nvidia --refresh to pull the latest catalog.

Slow responses: Nemotron-70b is a large model. If latency is a concern, switch to nemotron-nano-8b for lower-stakes tasks.


Further Reading


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