Model reference · open weights
Nemotron-3-Embed is an open-weight embedding model from nvidia, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
NVIDIA Nemotron 3 Embed Model Overview Description: Nemotron-3-Embed-1B-BF16 is a versatile text embedding model trained by NVIDIA and optimized for retrieval and semantic similarity tasks. It provides strong multilingual and cross-lingual retrieval capabilities and is designed to serve as a foundational component in text-based Retrieval-Augmented Generation (RAG) systems. This model was evaluated across 34 languages: English, Arabic, Assamese, Bengali, Bulgarian, Chinese, Danish, Dutch, Finnish, French, German, Hindi, Hinglish, Indonesian, Italian, Japanese, Korean, Malay, Marathi, Nepali, Norwegian, Persian, Portuguese, Romanian, Russian, Spanish, Swahili, Swedish, Tamil, Telugu, Thai, Ukrainian, Urdu, Vietnamese. The model generates dense vector embeddings from multilingual text inputs, enabling retrieval, semantic search, and (agentic) RAG workflows. As a core component of text retrieval systems, an embedding model transforms text, such as questions or passages, into dense vector representations. These models are typically transformer encoders that process input tokens and produce embeddings suitable for efficient similarity matching. Among models of comparable size, Nemotron-3-Embed-1B-BF16 achieves state-of-the-art performance across multiple multilingual retrieval benchmarks. Read more details in our Blog Post. This model is ready for commercial use. License/Terms of Use: This model and its associated configuration files are licensed under the OpenMDW License Agreement, version 1.1 (OpenMDW-1.1). ADDITIONAL INFORMATION: Apache License, Version 2.0. This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use. Deployment Geography: Global Use Case: <br Nemotron-3-Embed-1B-BF16 is most suitable for users who want to build a multilingual question-and-answer application over a large text corpus, leveraging the latest dense retrieval technologies. Release Date: <br 07/16/2026 via https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16 Model Architecture: Architecture Type: Transformer <br Network Architecture: Ministral-3-3B-Instruct-2512 based pruned
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | nvidia |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 1.1B |
| Variants | 1 |
| Runs with | sentence-transformers |
| Based on | mistralai/Ministral-3-3B-Instruct-2512 |
| Released | 2026-07-14 |
| Popularity | 332k downloads / month |
| Likes | 145 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| Nemotron-3-Embed-1B-BF16 | 1.1B | BF16 | ~2.6 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys nemotron-3-embed for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (nemotron-3-embed below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"nemotron-3-embed","input":"text to embed"}'
Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗
Explore