Humanoid Locomotion
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 California (UC) Berkeley
- Organisation type
- Academia
- Country
- United States of America
- Published
- 29 February 2024
- Authors
- Ilija Radosavovic, Bike Zhang, Baifeng Shi, Jathushan Rajasegaran, Sarthak Kamat, Trevor Darrell, Koushil Sreenath, Jitendra Malik
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Robotics
- Task
- Animal (human/non-human) imitation
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
- 8M
- Training data
- tokens
Largest model trained has 8M params. Note actual model used in real-world experiments appears to be 2M, to improve latency. See sections 5.1 and 5.9.
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
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
- 108
Sources
Where this record came from and when it was last checked.
- Reference
- Humanoid Locomotion as Next Token Prediction
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
Humanoid Locomotion was published by University of California (UC) Berkeley, in United States of America, in February 2024. It comes out of academia.
It works in Robotics, and is recorded as doing animal (human/non-human) imitation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
Humanoid Locomotion — common questions
Is Humanoid Locomotion open source?
No. Humanoid Locomotion has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Humanoid Locomotion have?
Humanoid Locomotion has 8M parameters. Largest model trained has 8M params. Note actual model used in real-world experiments appears to be 2M, to improve latency. See sections 5.1 and 5.9. 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 Humanoid Locomotion?
Humanoid Locomotion was published by University of California (UC) Berkeley, based in United States of America, categorised as academia.
When was Humanoid Locomotion released?
Humanoid Locomotion was published in February 2024. 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 Humanoid Locomotion used for?
Humanoid Locomotion works in Robotics, and is recorded as handling animal (human/non-human) imitation. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Humanoid Locomotion?
None. Humanoid Locomotion 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.