BPL

Closed weights University of Toronto,New York University (NYU),Massachusetts Institute of Technology (MIT) December 2015

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 Toronto,New York University (NYU),Massachusetts Institute of Technology (MIT)
Organisation type
Academia,Academia,Academia
Country
Canada, United States of America
Published
11 December 2015
Authors
BM Lake, R Salakhutdinov, JB Tenenbaum

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Image generation
Task
Image generation

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

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Record confidence
Unknown
Citations
3,178

Sources

Where this record came from and when it was last checked.

Reference
Human-level concept learning through probabilistic program induction
Last updated
1 January 2026

What the numbers mean

Where it came from

BPL was published by University of Toronto,New York University (NYU),Massachusetts Institute of Technology (MIT), in Canada, in December 2015. It comes out of academia,Academia,Academia.

It works in Image generation, and is recorded as doing image generation.

Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.

Answers

BPL — common questions

01

When was BPL released?

BPL was published in December 2015. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

02

What is BPL used for?

BPL works in Image generation, and is recorded as handling image generation. 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.

03

What GPU do I need to run BPL?

None. BPL 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.

04

Is BPL open source?

The licensing for BPL was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.

05

How many parameters does BPL have?

No parameter count has been published for BPL, which is why no memory or speed figure appears on this page.

06

Who created BPL?

BPL was published by University of Toronto,New York University (NYU),Massachusetts Institute of Technology (MIT), based in Canada, categorised as academia,Academia,Academia.

Source

Original publication

Record last updated 1 January 2026

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.