VQ-VAE-2 (ImageNet)
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
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 June 2019
- Authors
- Ali Razavi, Aaron van den Oord, Oriol Vinyals
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Image generation
- Task
- Image generation
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
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
"ImageNet 256 × 256"
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
- Generating Diverse High-Fidelity Images with VQ-VAE-2
- Last updated
- 11 February 2026
What the numbers mean
Where it came from
VQ-VAE-2 (ImageNet) was published by Google, in United States of America, in June 2019. It comes out of industry.
It works in Image generation, and is recorded as doing image generation.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
VQ-VAE-2 (ImageNet) — common questions
What is VQ-VAE-2 (ImageNet) used for?
VQ-VAE-2 (ImageNet) works in Image generation, and is recorded as handling image generation. 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.
What GPU do I need to run VQ-VAE-2 (ImageNet)?
None. VQ-VAE-2 (ImageNet) is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is VQ-VAE-2 (ImageNet) open source?
No. VQ-VAE-2 (ImageNet) has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does VQ-VAE-2 (ImageNet) have?
No parameter count has been published for VQ-VAE-2 (ImageNet), which is why no memory or speed figure appears on this page.
Who created VQ-VAE-2 (ImageNet)?
VQ-VAE-2 (ImageNet) was published by Google, based in United States of America, categorised as industry.
When was VQ-VAE-2 (ImageNet) released?
VQ-VAE-2 (ImageNet) was published in June 2019. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.