Visual document searchSearch and RAG

VLM2Vec

Turns an image-plus-text model into an embedding model: one vector for a page, a diagram or a captioned photo. The card states English.

Developer
TIGER-Lab, Canada
First release
Oct 2024
Latest release
Oct 2024
Sizes
about 4B (based on Phi-3.5-V)
License
Commercial use allowedApache 2.0
Russian
Not supported
Running
On your own serverNeeds a GPU
Industries
Documents and accounting, Retail and marketplaces, Science and research, Media and production
Deploy on your server Hugging Face GitHub

What it does

  • Search across a mixed archive of texts and images
  • Search across document pages as images
  • Finding similar cards and illustrations

Where it is used

Document managementE-commerceResearch and science

Hardware requirements

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

Versions

  1. VLM2Vec-Full и VLM2Vec-LoRA

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.

Frequently asked questions

Can VLM2Vec be used in a commercial project?

Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does VLM2Vec need?

At minimum: One GPU with 16–80 GB — mid-size 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 VLM2Vec support Russian?

No. The developer documentation lists the supported languages and Russian is not among them.

Where can I download VLM2Vec and what does it cost?

The VLM2Vec 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

Visual document searchGME (General Multimodal Embedding)Alibaba (Tongyi Lab) · ChinaCommercial use allowed

One vector for text, for an image and for a text-image pair: a single model can find a product by photo, a document page by question and an image by description. The card lists English and Chinese.

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.

DetailsComputer visionSigLIP (наследник CLIP)Google · USACommercial use allowed

Models that map images and text into a shared space: you can search photos by words and classify images without training. OpenAI's CLIP (2021) is the predecessor.

Details

Source: huggingface.co/TIGER-Lab/VLM2Vec-Full. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.