How do I get started with NVIDIA Build?
Three steps. About 3 minutes.
Step 1: Sign up at build.nvidia.com
Go to build.nvidia.com and create a free account. NVIDIA awards starter credits — enough to run thousands of API calls before you spend a cent.
Step 2: Generate an API key
In your dashboard, hit "Get API Key" and copy the token. Set it as an env variable:
bash
export NVIDIA_API_KEY="nvapi-xxxxx"
Step 3: Hit the OpenAI-compatible endpoint
bash
curl https://integrate.api.nvidia.com/v1/chat/completions \
-H "Authorization: Bearer $NVIDIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "meta/llama-3.1-405b-instruct",
"messages": [{"role":"user","content":"Hello"}]
}'
Step 4: Pick a model from the catalog
Browse build.nvidia.com/explore — the catalog includes:
| Family | Notable models |
|---|---|
| Meta | Llama 3.1 405B, Llama 3.3 70B |
| OpenAI | gpt-oss-120b, gpt-oss-20b |
| NVIDIA | Nemotron-3-Nano-Omni-30B, Nemotron-4-340B |
| ByteDance | Seedance, Doubao open-weights |
| Mistral | Mistral Large 2, Mixtral |
| DeepSeek | DeepSeek-R1, DeepSeek-V3 |
Step 5: Wire it into your favorite tool
Because the API is OpenAI-compatible, point any OpenAI client at the NVIDIA base URL:
python
from openai import OpenAI
client = OpenAI(
base_url="https://integrate.api.nvidia.com/v1",
api_key=os.environ["NVIDIA_API_KEY"]
)
response = client.chat.completions.create(
model="meta/llama-3.1-405b-instruct",
messages=[{"role": "user", "content": "Write a poem about GPUs"}]
)
This means you can use NVIDIA Build with LangChain, LlamaIndex, n8n's OpenAI node, Claude Code's external-model wrapper, or any tool that speaks OpenAI's API.
Step 6: Build a Blueprint (optional)
NVIDIA Blueprints are pre-built reference apps — RAG, digital humans, summarization, etc. They run on the same free credits.
What is NVIDIA Build?
NVIDIA Build is NVIDIA's developer platform for trying NIM (NVIDIA Inference Microservices) APIs. The pitch: "Try NVIDIA NIM APIs" — meaning you call top open-weight models through NVIDIA's optimized inference stack without provisioning a single GPU.
The catalog is huge. Top model families include Meta's Llama, OpenAI's open-weights, NVIDIA's Nemotron, ByteDance models, Mistral, and DeepSeek.
Is NVIDIA Build really free?
Largely yes — for evaluation and prototyping. NVIDIA awards starter credits when you sign up, and many models have free endpoints visible on the model catalog. Once you scale past the free tier, it becomes pay-as-you-go at competitive rates.
For comparison: Claude Pro is $20/month for limited Claude API use, Claude Max is $100/month. NVIDIA Build gives you Llama 3.1 405B and Nemotron 340B for $0 starter credit. For a builder testing ideas, that gap is enormous.
How is NVIDIA Build different from Claude Code's API?
Three differences:
- Model breadth. Claude Code is Claude only. NVIDIA Build hosts Llama, Mistral, DeepSeek, Nemotron, OpenAI's open-weights, ByteDance, and dozens more.
- OpenAI-compatible. The API mirrors OpenAI's, so any OpenAI SDK works out of the box.
- Free starter credits. Real free, not a 7-day trial. Run experiments for weeks before you decide what to pay for.
The trade: Claude is genuinely the best model for many tasks (code, long-context reasoning, design output with Impeccable). NVIDIA Build does not replace Claude — it complements it for everything else.
What's the catch?
- Free credits run out. Eventually you graduate to paid usage. Plan for it.
- Rate limits exist. Some models are throttled on the free tier. Build with retry/backoff.
- No Claude on the catalog. If your workflow needs Claude specifically, you still need Anthropic. NVIDIA Build is the rest of the model universe.
Bottom line
If you have not signed up for NVIDIA Build yet, you are leaving real money on the table. Free access to Llama 3.1 405B alone is worth the click. Pair it with n8n for orchestration and Impeccable for design and you have a top-tier AI stack at near-zero cost.
Related Nanoflow guides
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