Model reference · open weights
llama-nemotron-embed-vl 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
Model Overview Description: llama-nemotron-embed-vl-1b-v2 was developed by NVIDIA for multimodal question-answering retrieval. The model can embed document pages in the form of image, text, or combined image–text inputs. Documents can be retrieved given a user query in text form. The model supports page images containing text, tables, charts, and infographics. We report the evaluation of this model on two internal multimodal retrieval benchmarks, and on the popular ViDoRe V1 and V2 benchmarks and the new Vidore V3 benchmark. An embedding model is a crucial component of a retrieval system because it transforms information into dense vector representations. An embedding model is typically a transformer encoder that processes tokens of input text or images (for example, questions, passages, or page images) to output an embedding. llama-nemotron-embed-vl-1b-v2 is a combined language and vision model. The llama-nemotron-embed-vl-1b-v2 is part of the Nemotron RAG collection of open models available on HuggingFace. It is also available for optimized inference as a NIM (NVIDIA Inference Microservice) from NVIDIA NeMo Retriever, which provides state-of-the-art, commercially-ready models and microservices optimized for the lowest latency and highest throughput. It features a production-ready information retrieval pipeline with enterprise support. The models that form the core of this solution have been trained using responsibly selected, auditable data sources. With multiple pre-trained models available as starting points, developers can readily customize them for domain-specific use cases, such as information technology, human resource help assistants, and research & development research assistants. This model is ready for commercial use. License/Terms of use The use of this model is governed by the NVIDIA Open Model License Agreement and the use of the post-processing scripts are licensed under Apache 2.0. Additional Information: Llama 3.2 Community Model License Agreement. Built with Llama. Deployment Geography: Global <br Use Case: <br The llama-nemotron-embed-vl-1b-v2 is suitable for users who want to build a multimodal question-and-answer application over a large co
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | nvidia |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 1.7B |
| Variants | 1 |
| Runs with | sentence-transformers |
| Released | 2025-12-03 |
| Popularity | 54k downloads / month |
| Likes | 100 |
| 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 |
|---|---|---|---|---|---|
| llama-nemotron-embed-vl-1b-v2 | 1.7B | BF16 | ~3.9 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys llama-nemotron-embed-vl for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (llama-nemotron-embed-vl 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":"llama-nemotron-embed-vl","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 ↗
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