GRUs

Closed weights University of Montreal / Université de Montréal,Jacobs University,University of Maine June 2014

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
University of Montreal / Université de Montréal,Jacobs University,University of Maine
Organisation type
Academia,Academia,Academia
Country
Canada, Germany, United States of America
Published
3 June 2014
Authors
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio

What it does

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

Domain
Language
Task
Language modeling, Translation

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

How it is classified

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

Why it is tracked
Highly cited
Record confidence
Unknown
Citations
26,262

Sources

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

Reference
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Last updated
25 May 2026

What the numbers mean

What this model is

GRUs was published by University of Montreal / Université de Montréal,Jacobs University,University of Maine, in Canada, in June 2014. It comes out of academia,Academia,Academia.

It works in Language, and is recorded as doing language modeling, Translation.

Its weights were never published, so it can only be reached through its provider. No graphics card changes that.

Training and provenance

It is tracked in the underlying dataset for one reason in particular: highly cited.

Answers

GRUs — common questions

01

When was GRUs released?

GRUs was published in June 2014. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

02

What is GRUs used for?

GRUs works in Language, and is recorded as handling language modeling, Translation. These are the areas it was designed around; they describe intent rather than a hard boundary.

03

What GPU do I need to run GRUs?

None. GRUs 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.

04

Is GRUs open source?

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

05

How many parameters does GRUs have?

No parameter count has been published for GRUs, which is why no memory or speed figure appears on this page.

06

Who created GRUs?

GRUs was published by University of Montreal / Université de Montréal,Jacobs University,University of Maine, based in Canada, categorised as academia,Academia,Academia.

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.