Gemini Robotics 1.5

Closed weights Google DeepMind September 2025

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
Google DeepMind
Organisation type
Industry
Country
United States of America
Published
25 September 2025
Authors
Abbas Abdolmaleki, Saminda Abeyruwan, Joshua Ainslie, Jean-Baptiste Alayrac, Montserrat Gonzalez Arenas, Ashwin Balakrishna, Nathan Batchelor, Alex Bewley, Jeff Bingham, Michael Bloesch, Konstantinos Bousmalis, Philemon Brakel, Anthony Brohan, Thomas Buschmann, Arunkumar Byravan, Serkan Cabi, Ken Caluwaerts, Federico Casarini, Christine Chan, Oscar Chang, London Chappellet-Volpini, Jose Enrique Ch…

What it does

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

Domain
Robotics, Vision, Language
Task
Robotic manipulation, Instruction interpretation

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

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
Google TPU v4,Google TPU v5e,Google TPU v6e Trillium

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

Gemini Robotics 1.5 is currently available to select partners.

How it is classified

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

Record confidence
Unknown

Sources

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

Reference
Gemini Robotics 1.5 brings AI agents into the physical world
Last updated
28 November 2025

What the numbers mean

Where it came from

Gemini Robotics 1.5 was published by Google DeepMind, in United States of America, in September 2025. It comes out of industry.

It works in Robotics, Vision, Language, and is recorded as doing robotic manipulation, Instruction interpretation.

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

Answers

Gemini Robotics 1.5 — common questions

01

When was Gemini Robotics 1.5 released?

Gemini Robotics 1.5 was published in September 2025.

02

What is Gemini Robotics 1.5 used for?

Gemini Robotics 1.5 works in Robotics, Vision, Language, and is recorded as handling robotic manipulation, Instruction interpretation. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.

03

What GPU do I need to run Gemini Robotics 1.5?

None. Gemini Robotics 1.5 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 Gemini Robotics 1.5 open source?

No. Gemini Robotics 1.5 has not had its weights published, so it exists only as a service controlled by its owner.

05

How many parameters does Gemini Robotics 1.5 have?

No parameter count has been published for Gemini Robotics 1.5, which is why no memory or speed figure appears on this page.

06

Who created Gemini Robotics 1.5?

Gemini Robotics 1.5 was published by Google DeepMind, based in United States of America, categorised as industry.

Source

Original publication

Record last updated 28 November 2025

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.