Description

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Overview

@sateeshreddy/n8n-nodes-nvidia-nim is an n8n community node package that gives you access to NVIDIA NIM’s free hosted models directly inside your workflows.

This package includes two nodes:

| Node | Purpose |
|—|—|
| NVIDIA NIM | Language model — connects to AI Agent, LLM Chain, etc. |
| NVIDIA NIM Embeddings | Embeddings model — connects to Qdrant, Pinecone, PGVector, Supabase, Weaviate, etc. |

Why use this?

• ✅ Free tier models via build.nvidia.com
• ✅ Language model node — plugs into AI Agent, Basic LLM Chain, Summarization Chain
• ✅ Embeddings node — plugs into any n8n vector store (Qdrant, Pinecone, PGVector, Supabase, Weaviate, Chroma)
• ✅ Supports 17 latest chat models including DeepSeek v4, Nemotron-3, Mistral, and Gemma 4
• ✅ Smart Defaults: Automatically updates optimal temperature and max tokens when a chat model is selected
• ✅ Supports 5 embedding models including free hosted endpoints
• ✅ Drop-in OpenAI-compatible API — no extra setup

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Supported Models

Chat / Language Models

When you select a model, the node will automatically configure the recommended max_tokens and temperature to provide the best results out of the box. You can still override these manually.

| Model ID | Default Max Tokens | Default Temperature |
|—|—|—|
| minimaxai/minimax-m3 | 8192 | 1 |
| nvidia/nemotron-3-ultra-550b-a55b | 16384 | 1 |
| stepfun-ai/step-3.7-flash | 16384 | 1 |
| moonshotai/kimi-k2.6 | 16384 | 1 |
| mistralai/mistral-medium-3.5-128b | 16384 | 0.7 |
| mistralai/mistral-nemotron | 4096 | 0.6 |
| sarvamai/sarvam-m | 16384 | 0.5 |
| nvidia/nemotron-3-nano-30b-a3b | 16384 | 1 |
| stepfun-ai/step-3.5-flash | 16384 | 1 |
| qwen/qwen3.5-122b-a10b | 16384 | 0.6 |
| nvidia/nemotron-3-super-120b-a12b | 16384 | 1 |
| mistralai/mistral-small-4-119b-2603 | 16384 | 0.1 |
| google/gemma-4-31b-it | 16384 | 1 |
| minimaxai/minimax-m2.7 | 8192 | 1 |
| z-ai/glm-5.1 | 16384 | 1 |
| deepseek-ai/deepseek-v4-pro | 16384 | 1 |
| deepseek-ai/deepseek-v4-flash | 16384 | 1 |

Embedding Models

| Model | Value | Note |
|—|—|—|
| NV Embed v1 (default) | nvidia/nv-embed-v1 | Free hosted endpoint |
| NV EmbedQA E5 v5 | nvidia/nv-embedqa-e5-v5 | Best for RAG / QA pipelines |
| Llama Nemotron Embed 1B v2 | nvidia/llama-nemotron-embed-1b-v2 | Multilingual, 26 languages |
| Llama Nemotron Embed VL 1B v2 | nvidia/llama-nemotron-embed-vl-1b-v2 | Multimodal (text + image docs) |
| BGE-M3 | BAAI/bge-m3 | Dense + multi-vector + sparse retrieval |

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Installation

Via n8n Community Nodes (Recommended)

1. Open your n8n instance
2. Go to Settings → Community Nodes
3. Click Install
4. Enter @sateeshreddy/n8n-nodes-nvidia-nim and confirm

Manual Installation

Navigate to your n8n custom nodes directory and install:

cd ~/.n8n/custom/
npm install @sateeshreddy/n8n-nodes-nvidia-nim

Then restart n8n.

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Getting Your API Key

1. Visit build.nvidia.com
2. Sign in or create a free account
3. Navigate to API Keys in your dashboard
4. Generate a new key and copy it

> Note: The free tier gives you a generous number of inference credits — no credit card required.

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Usage

Setting Up Credentials

In n8n, go to Credentials → New → NVIDIA NIM API and paste your API key. Both the chat node and the embeddings node share the same credential.

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NVIDIA NIM (Chat / Language Model)

Use this node anywhere n8n expects a language model.

1. Add an AI Agent (or Basic LLM Chain) node to your workflow
2. In the Model slot, click +
3. Search for NVIDIA NIM and select it
4. Choose your model — the optimal temperature and max tokens will be populated automatically!
5. Run your workflow

Configuration Options:

| Parameter | Type | Default | Description |
|—|—|—|—|
| Model | Dropdown | deepseek-ai/deepseek-v4-flash | The NIM chat model to use |
| Temperature | Number | Dynamic | Controls output randomness. Automatically updates based on the model chosen. |
| Max Tokens | Number | Dynamic | Maximum tokens in the response. Automatically updates based on the model chosen. |

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NVIDIA NIM Embeddings

Use this node anywhere n8n expects an embeddings model — vector stores like Qdrant, Pinecone, PGVector, Supabase, Weaviate, and Chroma.

1. Add a Qdrant Vector Store (or any other vector store) node
2. In the Embeddings slot, click +
3. Search for NVIDIA NIM Embeddings and select it
4. Choose your embedding model
5. Run your workflow

Configuration Options:

| Parameter | Type | Default | Description |
|—|—|—|—|
| Model | Dropdown | nvidia/nv-embed-v1 | The NIM embedding model to use |

Compatible vector stores: Qdrant · Pinecone · PGVector · Supabase · Weaviate · Chroma

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Contributing

Pull requests are welcome! To add a new model, fix a bug, or improve documentation:

1. Fork the repo
2. Create a feature branch
3. Commit your changes
4. Push and open a PR

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License

MIT

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