DeepFace
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
- Tel Aviv University,Facebook
- Organisation type
- Academia,Industry
- Country
- Israel, United States of America
- Published
- 23 June 2014
- Authors
- Y Taigman, M Yang, MA Ranzato
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Face verification
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
- 4,400,000 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
- Highly cited
- Record confidence
- Unknown
- Citations
- 6,398
Sources
Where this record came from and when it was last checked.
- Reference
- DeepFace: Closing the Gap to Human-Level Performance in Face Verification
- Last updated
- 1 January 2026
What the numbers mean
What this model is
DeepFace was published by Tel Aviv University,Facebook, in Israel, in June 2014. academia,Industry is the category the publisher falls under.
It works in Vision, and is recorded as doing face verification.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The training set ran to roughly 4,400,000 tokens.
The reason it appears in this catalogue at all is highly cited.
Answers
DeepFace — common questions
Is DeepFace open source?
The licensing for DeepFace 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 DeepFace have?
No parameter count has been published for DeepFace, which is why no memory or speed figure appears on this page.
Who created DeepFace?
DeepFace was published by Tel Aviv University,Facebook, based in Israel, categorised as academia,Industry.
When was DeepFace released?
DeepFace was published in June 2014. 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 DeepFace used for?
DeepFace works in Vision, and is recorded as handling face verification. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run DeepFace?
None. DeepFace 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.