Search and RAG

Nomic Embed

Fully open embeddings, with weights, data and training code. v2 is multilingual on MoE; there are versions for code and for searching PDF pages.

Developer
Nomic AI, USA
First release
Jan 2024
Latest release
Mar 2025
Sizes
137M – 7B
License
Commercial use allowedApache 2.0 (some multimodal versions follow the base model's terms)
Russian
Supported
Ready-made builds
GGUF, MLX (Apple)
Running
Available in OllamaAlso runs without a GPU
Industries
Software development, Customer support, Documents and accounting
Deploy on your server Hugging Face GitHub

What it does

  • Search across documents and a knowledge base
  • Code search
  • Search across scans and PDFs without text recognition

Where it is used

IT departmentsCustomer supportDocument management

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. nomic-embed-code и multimodal
  2. nomic-embed-text v2 (MoE)
  3. nomic-embed-vision
  4. v1.5
  5. nomic-embed-text v1

How to run it

With Ollama — the fastest wayInstall Ollama on your computer or server and find the model in its library by name. Good enough to try the model on your own tasks in one evening.Find it in the Ollama library
On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can Nomic Embed be used in a commercial project?

Yes. License: Apache 2.0 (some multimodal versions follow the base model's terms). It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does Nomic Embed need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does Nomic Embed support Russian?

Yes, Russian is listed on the model card.

Where can I download Nomic Embed and what does it cost?

The Nomic Embed weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

Similar models

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DetailsSearch and RAGGTEAlibaba · ChinaCommercial use allowed

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DetailsSearch and RAGJina EmbeddingsJina AI · GermanyCommercial use with conditions

Strong multilingual embeddings with long context; v5-omni understands text, images and audio. Recent versions are open for non-commercial use only.

Details

Source: huggingface.co/nomic-ai/nomic-embed-code. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.