Context-dependent RNN
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
- Microsoft Research,Brno University of Technology
- Organisation type
- Industry,Academia
- Country
- United States of America, Czechia
- Published
- 27 July 2012
- Authors
- Tomas Mikolov, Geoffrey Zweig
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
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
- 37,000,000 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
- SOTA improvement
- Record confidence
- Unknown
- Citations
- 707
New SOTA perplexity on PTB
Sources
Where this record came from and when it was last checked.
- Reference
- Context Dependent Recurrent Neural Network Language Model
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Context-dependent RNN was published by Microsoft Research,Brno University of Technology, in the country recorded as United States of America, during July 2012. It comes out of an organisation categorised as industry,Academia.
It works in the domain of Language, and is recorded as performing the task of language modeling.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
The training set ran to roughly 37,000,000 tokens of text.
It is tracked in the underlying dataset for one reason in particular: sOTA improvement.
Answers
Context-dependent RNN — common questions
Context-dependent RNN— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Context-dependent RNN— 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.
Context-dependent RNN— who created it?
It was published by Microsoft Research,Brno University of Technology, based in United States of America, an organisation categorised as industry,Academia.
Context-dependent RNN— when was it released?
It was published in July 2012. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Context-dependent RNN— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling. These are the areas it was designed around; they describe intent rather than a hard boundary.
Context-dependent RNN— what GPU do I need to run it?
None. This 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.