Rubik's cube ADR robot
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
- OpenAI
- Organisation type
- Industry
- Country
- United States of America
- Published
- 15 October 2019
- Authors
- Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, Lei Zhang
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Robotics
- Task
- Robotic manipulation
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
- 27.8M
- Training data
- tokens
Table 13 on pg. 44 of the Cube paper, saved in "RL papers" folder. Sum of all the trainable parameters (dominated by the value and policy networks). source: https://docs.google.com/spreadsheets/d/1Kj4Q5WADcDXtUJLIOfGTCE3tGvxNczEMwyy8QtgSkHk/edit#gid=54587040&fvid=1361937389
" The cumulative amount of experience over that period used for training on the Rubik’s cube is roughly 13 thousand years, which is on the same order of magnitude as the 40 thousand years used by OpenAI Five" 13/40 * 1.92e8 = 6.24e7 EDIT 2024-05-30: OpenAI Five entry was updated in 2022 to reflect a better understanding of dataset, true size is on the order of 4.5e11 13/40 * 4.5e11 = 1.46e11
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
- 8.5 × 10²⁰ FLOP
- How it was established
- Third-party estimation
source: https://docs.google.com/spreadsheets/d/1Kj4Q5WADcDXtUJLIOfGTCE3tGvxNczEMwyy8QtgSkHk/edit#gid=54587040&fvid=1361937389
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA Tesla V100 DGXS 32 GB
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
- Citations
- 1,359
Sources
Where this record came from and when it was last checked.
- Reference
- Solving Rubik’s Cube with a Robot Hand
- Last updated
- 1 January 2026
What the numbers mean
What this model is
Rubik's cube ADR robot was published by OpenAI, in United States of America, in October 2019. The organisation is categorised as industry.
It works in Robotics, and is recorded as doing robotic manipulation.
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
Training it took roughly 8.5 × 10²⁰ FLOP of computation, on NVIDIA Tesla V100 DGXS 32 GB — a measure of what producing the model cost, not of how fast it answers.
Answers
Rubik's cube ADR robot — common questions
Is Rubik's cube ADR robot open source?
No. Rubik's cube ADR robot has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Rubik's cube ADR robot have?
Rubik's cube ADR robot has 27.8M parameters. Table 13 on pg. 44 of the Cube paper, saved in "RL papers" folder. Sum of all the trainable parameters (dominated by the value and policy networks). source: https://docs.google.com/spreadsheets/d/1Kj4Q5WADcDXtUJLIOfGTCE3tGvxNczEMwyy8QtgSkHk/edit#gid=54587040&fvid=1361937389. 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 Rubik's cube ADR robot?
Rubik's cube ADR robot was published by OpenAI, based in United States of America, categorised as industry.
When was Rubik's cube ADR robot released?
Rubik's cube ADR robot was published in October 2019. 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 Rubik's cube ADR robot used for?
Rubik's cube ADR robot works in Robotics, and is recorded as handling robotic manipulation. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
How much compute was used to train Rubik's cube ADR robot?
Around 8.5 × 10²⁰ FLOP, on NVIDIA Tesla V100 DGXS 32 GB. 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 Rubik's cube ADR robot?
None. Rubik's cube ADR robot 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.