Model reference · open weights

Virchow

Embeddings paige-ai Image embed 1 build Open weights 7k dl/mo

Virchow is an open-weight embedding model from paige-ai. Virchow (FP32) weighs 1.3 GB; the smallest configuration that runs it is RTX 3060 12 GB.

  • Virchow is a self-supervised vision transformer developed by paige-ai for image feature extraction in computational pathology.
  • The model has 631M parameters and uses a ViT-H/14 architecture with a 224x224 image size.
  • It is licensed under Apache 2.0.

Summary of the paige-ai/Virchow model card, 2026-10-01

What it is

Released bypaige-ai
Released2024-06-05
Parameters631M
VRAM1.3 GB for the weights

What it runs on

Memory and cards for Virchow (FP32)

1.3 GBweights, file size
1.1 GBruntime overhead
CardRunsMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together, which is the basis of search and RAG.
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