LDA
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
- Stanford University
- Organisation type
- Academia
- Country
- United States of America
- Published
- 2 February 2003
- Authors
- David M. Blei, Andrew Y. Ng, Michael I. Jordan
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Document classification
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
Multiple experiments with different tasks and datasets
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
- 38,724
Sources
Where this record came from and when it was last checked.
- Reference
- Latent Dirichlet Allocation
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
LDA was published by Stanford University, in United States of America, in February 2003. It comes out of academia.
It works in Language, and is recorded as doing document classification.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
How it was trained
Its inclusion criterion is highly cited.
Answers
LDA — common questions
Who created LDA?
LDA was published by Stanford University, based in United States of America, categorised as academia.
When was LDA released?
LDA was published in February 2003. 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 LDA used for?
LDA works in Language, and is recorded as handling document classification. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run LDA?
None. LDA 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 LDA open source?
The licensing for LDA was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does LDA have?
No parameter count has been published for LDA, which is why no memory or speed figure appears on this page.
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.