SIMA 2
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
- 4 December 2025
- Authors
- Adrian Bolton, Alexander Lerchner, Alexandra Cordell, Alexandre Moufarek, Andrew Bolt, Andrew Lampinen, Anna Mitenkova, Arne Olav Hallingstad, Bojan Vujatovic, Bonnie Li, Cong Lu, Daan Wierstra, Daniel P. Sawyer, Daniel Slater, David Reichert, Davide Vercelli, Demis Hassabis, Drew A. Hudson, Duncan Williams, Ed Hirst, Fabio Pardo, Felix Hill, Frederic Besse, Hannah Openshaw, Harris Chan, Hubert So…
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- 3D modeling
- Base model
- Gemini 2.5 Flash-Lite
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
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.
- Why it is tracked
- Discretionary
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- SIMA 2: A Generalist Embodied Agent for Virtual Worlds
- Last updated
- 8 April 2026
What the numbers mean
What this model is
SIMA 2 was published by Google DeepMind, in the country recorded as United States of America, during December 2025. It comes out of an organisation categorised as industry.
It works in the domain of 3D modeling.
It builds on Gemini 2.5 Flash-Lite. Most models at this scale are adapted from an existing base rather than built from nothing.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Training and provenance
Its inclusion criterion: discretionary.
Answers
SIMA 2 — common questions
SIMA 2— what is it used for?
It works in the domain of 3D modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
SIMA 2— what GPU do I need to run it?
None. This 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.
SIMA 2— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
SIMA 2— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
SIMA 2— who created it?
It was published by Google DeepMind, based in United States of America, an organisation categorised as industry.
SIMA 2— when was it released?
It was published in December 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.