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description: "NVIDIA Cloud — build.nvidia.com API, NIM containers for self-hosted inference, NeMo for training, DGX Cloud"
mode: subagent
tools:
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---

<!-- SPDX-License-Identifier: MIT -->
<!-- SPDX-FileCopyrightText: 2025-2026 Marcus Quinn -->

# NVIDIA Cloud

<!-- AI-CONTEXT-START -->

## Quick Reference

- **Cloud API**: `https://integrate.api.nvidia.com/v1` (OpenAI-compat, prototyping)
- **Auth**: API key from [build.nvidia.com](https://build.nvidia.com/) (free, 1000 credits)
- **Creds**: `NVIDIA_API_KEY` env var | `Authorization: Bearer <key>` header
- **Self-host**: NIM containers via `docker pull nvcr.io/nim/<model>` (requires NGC API key)
- **Docs**: [docs.api.nvidia.com](https://docs.api.nvidia.com/) | [NIM docs](https://docs.nvidia.com/nim/) | [build.nvidia.com](https://build.nvidia.com/explore/discover)
- **Pricing**: Cloud API free (1000 credits, replenishable). NIM self-host free with AI Enterprise license or DGX. No published per-token serverless pricing.

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NVIDIA's AI inference platform: (1) free cloud API for prototyping at build.nvidia.com, (2) self-hosted NIM containers for production on your own GPUs. OpenAI SDK compatible. DGX Cloud available for GPU rental (contact sales).

**Best for**: prototyping with free credits, self-hosted production inference (NIM containers are highly optimized), NVIDIA GPU owners (DGX, HGX), healthcare/biology/simulation models, enterprise with AI Enterprise licenses.
**Not for**: pay-per-token production serverless (no published pricing), fine-tuning via API (use NeMo separately), budget-conscious serverless (use Fireworks/Together), edge inference (use Cloudflare), privacy-critical with TEE (use NEAR AI).

## Models (100+)

### LLMs

DeepSeek V3.1/V3.2, Llama 2/3/3.1/3.2/3.3/4, Mistral/Mixtral family, Qwen 2/2.5/3/3.5, GPT-OSS 20B/120B, Nemotron family (NVIDIA's own), Kimi K2, MiniMax M2.5, GLM-4.7/5, Phi-3/4, Gemma 2/3/3n, Granite, and many more.

### Specialized

- **Retrieval**: Embeddings (NV-Embed, BGE, Arctic), reranking (NV-Rerank, BGE)
- **Vision**: FLUX image gen, Stable Diffusion, object detection, document parsing
- **Healthcare**: AlphaFold2, ESMFold, protein design (RFDiffusion, ProteinMPNN), molecular docking
- **Simulation**: Weather prediction (FourCastNet), climate (CorrDiff)
- **Safety**: NemoGuard (jailbreak detection, content safety, topic control), Llama Guard
- **Code**: StarCoder2, Codestral, CodeGemma

## Usage

### Cloud API (prototyping)

```bash
curl https://integrate.api.nvidia.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $NVIDIA_API_KEY" \
  -d '{"model": "meta/llama-3.3-70b-instruct", "messages": [{"role": "user", "content": "Hello"}]}'
```

```python
# OpenAI SDK (change base_url only)
from openai import OpenAI
client = OpenAI(api_key=os.environ["NVIDIA_API_KEY"], base_url="https://integrate.api.nvidia.com/v1")
response = client.chat.completions.create(
    model="meta/llama-3.3-70b-instruct",
    messages=[{"role": "user", "content": "Hello"}]
)
```

### Self-hosted NIM (production)

```bash
# Pull and run NIM container (requires NGC API key and NVIDIA GPU)
export NGC_API_KEY="<your-ngc-api-key>"
docker login nvcr.io --username '$oauthtoken' --password "$NGC_API_KEY"

docker run --gpus all \
  -e NGC_API_KEY="$NGC_API_KEY" \
  -p 8000:8000 \
  nvcr.io/nim/meta/llama-3.3-70b-instruct:latest

# Query (same OpenAI-compatible API)
curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model": "meta/llama-3.3-70b-instruct", "messages": [{"role": "user", "content": "Hello"}]}'
```

NIM containers include NVIDIA's inference optimizations (TensorRT-LLM, quantization, batching). Generally faster than vLLM/TGI for NVIDIA GPUs. NIM has no built-in auth — run behind a reverse proxy.

## Limitations (cloud API)

- No fine-tuning — use NeMo (separate product) or Fireworks/Together
- No batch inference API — use Fireworks/Together
- No dedicated cloud deployments with autoscaling — use Fireworks/Together or DGX Cloud
- No CLI tool — REST API and Docker only
- No audio/speech models — use Fireworks/Together/Cloudflare
- No Attestation/TEE guarantees — NVIDIA processes requests; use NEAR AI for TEE

## NeMo (Training)

Separate product for training and customization: NeMo Customizer (SFT, PEFT, DPO), Evaluator, Data Designer (synthetic datasets), Guardrails (safety/alignment). Self-hosted or via DGX Cloud. Not accessible through the build.nvidia.com API.

## Security

- Store API key: `aidevops secret set NVIDIA_API_KEY`
- NGC API key (for NIM pulls): `aidevops secret set NGC_API_KEY`
- Never expose keys in logs or output
- Self-hosted NIM: full data sovereignty, but run behind reverse proxy with auth (NIM has no built-in auth)
- Cloud API: NVIDIA processes requests (no TEE guarantees)

## See Also

- `tools/infrastructure/fireworks.md` -- managed serverless inference + fine-tuning
- `tools/infrastructure/together.md` -- managed inference + GPU clusters
- `tools/infrastructure/nearai.md` -- TEE-backed private inference
- `tools/infrastructure/cloud-gpu.md` -- raw GPU providers for self-hosting NIM
- `tools/deployment/hosting-comparison.md` -- full platform comparison
