BellKor 2008
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
- AT&T
- Organisation type
- Industry
- Country
- United States of America
- Published
- 1 August 2009
- Authors
- RM Bell, Y Koren, C Volinsky
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Recommendation
- Task
- Movie ratings
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
"Netflix provided a training data set of 100,480,507 ratings that 480,189 users gave to 17,770 movies."
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
- Citations
- 162
Won Netflix prize
Sources
Where this record came from and when it was last checked.
- Reference
- The BellKor 2008 Solution to the Netflix Prize
- Last updated
- 28 November 2025
What the numbers mean
About this model
BellKor 2008 was published by AT&T, in the country recorded as United States of America, during August 2009. It comes out of an organisation categorised as industry.
It works in the domain of Recommendation, and is recorded as performing the task of movie ratings.
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 reason it appears in this catalogue at all: sOTA improvement.
Answers
BellKor 2008 — common questions
BellKor 2008— 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.
BellKor 2008— who created it?
It was published by AT&T, based in United States of America, an organisation categorised as industry.
BellKor 2008— when was it released?
It was published in August 2009. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
BellKor 2008— what is it used for?
It works in the domain of Recommendation, and is recorded as handling the task of movie ratings. 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.
BellKor 2008— 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.
BellKor 2008— 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.
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.