AWD-LSTM
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
- DeepMind,University of Oxford
- Organisation type
- Industry,Academia
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 18 July 2017
- Authors
- Gábor Melis, Chris Dyer, Phil Blunsom
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
- Numerical format
- FP32
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
- 24M
- Training data
- 2,000,000 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
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
- SOTA improvement
- Record confidence
- Confident
- Citations
- 555
- Benchmark data
- AWD-LSTM
"We establish a new state of the art on the Penn Treebank and Wikitext-2 corpora"
Sources
Where this record came from and when it was last checked.
- Reference
- On the State of the Art of Evaluation in Neural Language Models
- Last updated
- 28 November 2025
What the numbers mean
Background
AWD-LSTM was published by DeepMind,University of Oxford, in United Kingdom of Great Britain and Northern Ireland, in July 2017. The organisation is categorised as industry,Academia.
It works in Language, and is recorded as doing language modeling.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
The training set ran to roughly 2,000,000 tokens.
Its inclusion criterion is sOTA improvement.
Answers
AWD-LSTM — common questions
Is AWD-LSTM open source?
No. AWD-LSTM has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does AWD-LSTM have?
AWD-LSTM has 24M parameters. 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.
Who created AWD-LSTM?
AWD-LSTM was published by DeepMind,University of Oxford, based in United Kingdom of Great Britain and Northern Ireland, categorised as industry,Academia.
When was AWD-LSTM released?
AWD-LSTM was published in July 2017. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is AWD-LSTM used for?
AWD-LSTM works in Language, and is recorded as handling language modeling. 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 AWD-LSTM?
None. AWD-LSTM 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.
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.