Rotation

Closed weights École des Ponts ParisTech 86M parameters March 2018

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
École des Ponts ParisTech
Organisation type
Academia
Country
France
Published
21 March 2018
Authors
Spyros Gidaris, Praveer Singh, Nikos Komodakis

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Image generation, Vision
Task
Image completion

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.

Parameters
86M

https://openai.com/blog/image-gpt/#rfref53

Training data
5,120,000 tokens

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Citations
3,575

Sources

Where this record came from and when it was last checked.

Reference
Unsupervised Representation Learning by Predicting Image Rotations
Last updated
25 May 2026

What the numbers mean

What this model is

Rotation was published by École des Ponts ParisTech, in France, in March 2018. It comes out of academia.

It works in Image generation, Vision, and is recorded as doing image completion.

Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.

Training and provenance

The training set ran to roughly 5,120,000 tokens.

Answers

Rotation — common questions

01

What GPU do I need to run Rotation?

None. Rotation 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.

02

Is Rotation open source?

The licensing for Rotation was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.

03

How many parameters does Rotation have?

Rotation has 86M parameters. https://openai.com/blog/image-gpt/#rfref53. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.

04

Who created Rotation?

Rotation was published by École des Ponts ParisTech, based in France, categorised as academia.

05

When was Rotation released?

Rotation was published in March 2018. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

06

What is Rotation used for?

Rotation works in Image generation, Vision, and is recorded as handling image completion. 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.

Source

Original publication

Record last updated 25 May 2026

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.