CXR Foundation
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Organisation type
- Industry
- Country
- United States of America
- Published
- 2 August 2024
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Medicine
- Task
- Image embedding, Image classification
- Base model
- EfficientNet-L2
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Open — downloadable
- Model access
- Open weights (restricted use)
- Hugging Face
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- CXR Foundation model card
- Last updated
- 28 November 2025
What the numbers mean
Background
CXR Foundation was published by Google, in the country recorded as United States of America, during August 2024. The publishing organisation is categorised as industry.
It works in the domain of Vision, Medicine, and is recorded as performing the task of image embedding, Image classification.
It builds on EfficientNet-L2. That is why it shares the base model's general shape and size.
Published weights mean the model runs on your machine rather than someone else's, which is what makes the hardware question below answerable at all. On Hugging Face it is published under the organisation google.
Answers
CXR Foundation — common questions
CXR Foundation— what GPU do I need to run it?
We cannot say. It has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
CXR Foundation— is it open source?
Its weights are published, so it can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
CXR Foundation— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
CXR Foundation— who created it?
It was published by Google, based in United States of America, an organisation categorised as industry.
CXR Foundation— when was it released?
It was published in August 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
CXR Foundation— what is it used for?
It works in the domain of Vision, Medicine, and is recorded as handling the task of image embedding, Image classification. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
CXR Foundation— where can I download it?
Its weights are published on Hugging Face, under the organisation google. We do not host model files — this site calculates what hardware is needed to run them.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.