RecommendersSearch and RAGComputer vision

Marqo Ecommerce Embeddings

Models that turn a product photo and its title into a single vector: suitable for a similar-items block, image search and matching by description. Built for retail product cards.

Developer
Marqo, Australia
First release
Aug 2024
Latest release
Nov 2024
Sizes
203M (B) и 652M (L)
License
Commercial use allowedApache 2.0
Russian
Not supported
Ready-made builds
8-bit, 4-bit
Running
On your own serverAlso runs without a GPU
Industries
Retail and marketplaces, Marketing and content, Media and production
Deploy on your server Hugging Face GitHub

What it does

  • Similar items by photo and title
  • Catalogue search by image
  • Product search from a shopper phrase
  • Finding duplicates in the catalogue

Where it is used

Online stores and marketplacesCatalogues and storefrontsMarketing and curated lists

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
no versions
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. Обновление карточек и сборок ONNX
  2. Marqo-Ecommerce-B и Marqo-Ecommerce-L
  3. Marqo-FashionSigLIP
  4. Marqo-FashionCLIP

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 Marqo Ecommerce Embeddings 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 Marqo Ecommerce Embeddings 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 Marqo Ecommerce Embeddings support Russian?

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

Where can I download Marqo Ecommerce Embeddings and what does it cost?

The Marqo Ecommerce Embeddings 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

RecommendersFashionCLIPFashionCLIP research project (Farfetch data) · not disclosedCommercial use allowed

A time-tested model for clothing and footwear: it places an item photo and its description in one space, so it fits similar-item blocks and outfit matching. Fine-tuning for your own assortment is advisable.

DetailsRecommendersBLaIRUC San Diego (McAuley Lab) · USACommercial use allowed

Light encoders trained on pairs of item card and real review: they produce item vectors for similar-item blocks and for search by a shopper description. The weights are small and run on an ordinary server.

DetailsRecommendersEasyRec (HKUDS)HKUDS, University of Hong Kong · ChinaCommercial use allowed

Encoders that put a text portrait of a shopper and a text description of an item into one vector space so they can be matched directly. They help where a new listing has no purchase statistics yet.

Details

Source: huggingface.co/Marqo/marqo-ecommerce-embeddings-L. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.