NPLM (AP News)
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
- Organisation type
- Academia
- Country
- Canada
- Published
- 15 March 2003
- Authors
- Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Jauvin
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Text autocompletion
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
- 11.9M
- Training data
- 13,994,528 tokens
"The number of free parameters is |V|(1 + nm + h) + h(1 + (n − 1)m) [...] For example, consider the following architecture used in the experiments on the AP (Associated Press) news data: the vocabulary size is |V| = 17,964, the number of hidden units is h = 60, the order of the model is n = 6, the number of word features is m = 100" AP News: n=6, h=60, m=100, |V|=17964 17964*(1+6*100+60)+60*(1+(6-1)*100)=11904264
"Comparative experiments were performed on the Brown corpus which is a stream of 1,181,041 words, from a large variety of English texts and books. The first 800,000 words were used for training, the following 200,000 for validation (model selection, weight decay, early stopping) and the remaining 181,041 for testing. The number of different words is 47,578 (including punctuation, distinguishing between upper and lower case, and including the syntactical marks used to separate texts and paragraph…
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 1.7 × 10¹⁵ FLOP
- How it was established
- Operation counting
"For example, consider the following architecture used in the experiments on the AP (Associated Press) news data: the vocabulary size is |V| = 17,964, the number of hidden units is h = 60, the order of the model is n = 6, the number of word features is m = 100. The total number of numerical operations to process a single training example is approximately |V|(1+nm+h)+h(1+nm)+nm" AP News: n=6, h=60, m=100, |V|=17964, dataset=13994528, epochs=5 Forward FLOP: 17964*(1+6*100+60)+60*(1+6*100)+6*100=1…
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Frontier model
- Yes
- Why it is tracked
- Highly cited
- Record confidence
- Confident
- Citations
- 7,637
Sources
Where this record came from and when it was last checked.
- Reference
- A Neural Probabilistic Language Model
- Last updated
- 11 February 2026
What the numbers mean
About this model
NPLM (AP News) was published by University of Montreal / Université de Montréal, in Canada, in March 2003. academia is the category the publisher falls under.
It works in Language, and is recorded as doing text autocompletion.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
Producing it required around 1.7 × 10¹⁵ FLOP of arithmetic, which is a statement about the training budget rather than about inference.
The training set ran to roughly 13,994,528 tokens.
It is tracked in the underlying dataset for one reason in particular: highly cited.
Answers
NPLM (AP News) — common questions
When was NPLM (AP News) released?
NPLM (AP News) was published in March 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 NPLM (AP News) used for?
NPLM (AP News) works in Language, and is recorded as handling text autocompletion. These are the areas it was designed around; they describe intent rather than a hard boundary.
How much compute was used to train NPLM (AP News)?
Around 1.7 × 10¹⁵ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
What GPU do I need to run NPLM (AP News)?
None. NPLM (AP News) 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 NPLM (AP News) open source?
The licensing for NPLM (AP News) 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 NPLM (AP News) have?
NPLM (AP News) has 11.9M parameters. "The number of free parameters is |V|(1 + nm + h) + h(1 + (n − 1)m) [...] For example, consider the following architecture used in the experiments on the AP (Associated Press) news data: the vocabulary size is |V| = 17,964, the number of hidden units is h = 60, the order of the model is n = 6, the number of word features is m = 100" AP News: n=6, h=60, m=100, |V|=17964 17964*(1+6*100+60)+60*(1+(6-1)*100)=11904264. 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 NPLM (AP News)?
NPLM (AP News) was published by University of Montreal / Université de Montréal, based in Canada, categorised as academia.
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.