RerankersVisual document search

Llama Nemotron Rerank

A small 1B reranker from NVIDIA. The vl version also takes document pages as images, not just text. The card states multilingual support without listing the languages.

Developer
NVIDIA, USA
First release
Oct 2025
Latest release
May 2026
Sizes
1B
License
Commercial use with conditionsNVIDIA proprietary license — see the model card for terms
Russian
Not stated
Ready-made builds
FP8
Running
On your own serverNeeds a GPU
Industries
Documents and accounting, Customer support, Software development, Manufacturing and logistics
Deploy on your server Hugging Face

What it does

  • Reordering passages before an AI assistant answers
  • Sorting retrieved scan and PDF pages
  • Search across internal policies and instructions

Where it is used

Document managementCustomer supportManufacturing and logistics

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. fp8-сборка vl-версии
  2. llama-nemotron-rerank-vl-1b-v2 (страницы-картинки)
  3. llama-nemotron-rerank-1b-v2

How to run it

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 Llama Nemotron Rerank be used in a commercial project?

With conditions. License: NVIDIA proprietary license — see the model card for terms. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does Llama Nemotron Rerank need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Without a GPU the model is not practical. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does Llama Nemotron Rerank support Russian?

The model card does not list languages, so Russian support cannot be promised — it has to be tested on your own examples.

Where can I download Llama Nemotron Rerank and what does it cost?

The Llama Nemotron Rerank 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

RerankersBGE RerankerBAAI (Beijing Academy of Artificial Intelligence) · ChinaCommercial use allowed

Rerankers: they take passages found by search and reorder them by how well they actually match the question. v2-m3 is multilingual and lightweight, often paired with bge-m3.

DetailsRerankersJina RerankerJina AI · GermanyCommercial use with conditions

Strong multilingual rerankers; m0 also ranks pages as images (scans, slides). The latest versions are open for non-commercial use only.

DetailsVisual document searchColPali / ColQwenIlluin Technology (ViDoRe team) · FranceCommercial use with conditions

Searches PDFs and scans as images: pages do not need to be OCR'd first, the model finds the right one for a question directly, including tables and charts. Trained on English.

Details

Source: huggingface.co/nvidia/llama-nemotron-rerank-vl-1b-v2-fp8. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.