SIMA
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
- 17 April 2024
- Authors
- SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Go…
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Games, Video
- Task
- Action recognition, Video description, Video
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
- 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
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- Scaling Instructable Agents Across Many Simulated Worlds
- Last updated
- 28 November 2025
What the numbers mean
What this model is
SIMA was published by Google DeepMind, in United States of America, in April 2024. It comes out of industry.
It works in Games, Video, and is recorded as doing action recognition, Video description, Video.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
SIMA — common questions
Who created SIMA?
SIMA was published by Google DeepMind, based in United States of America, categorised as industry.
When was SIMA released?
SIMA was published in April 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 SIMA used for?
SIMA works in Games, Video, and is recorded as handling action recognition, Video description, Video. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run SIMA?
None. SIMA 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.
Is SIMA open source?
No. SIMA has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does SIMA have?
No parameter count has been published for SIMA, which is why no memory or speed figure appears on this page.
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.