Muse Spark
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
- Meta AI
- Organisation type
- Industry
- Country
- United States of America
- Published
- 8 April 2026
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Multimodal, Language, Vision
- Task
- Language modeling/generation, Question answering
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
- API access
- Training code
- 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
- Confident
At release, flagship LLM of one of the largest AI companies in the world
Sources
Where this record came from and when it was last checked.
- Reference
- Introducing Muse Spark: Scaling Towards Personal Superintelligence
- Last updated
- 13 July 2026
What the numbers mean
Where it came from
Muse Spark was published by Meta AI, in the country recorded as United States of America, during April 2026. It comes out of an organisation categorised as industry.
It works in the domain of Multimodal, Language, Vision, and is recorded as performing the task of language modeling/generation, Question answering.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
It is tracked in the underlying dataset for one reason in particular: discretionary.
Answers
Muse Spark — common questions
Muse Spark— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Muse Spark— 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.
Muse Spark— who created it?
It was published by Meta AI, based in United States of America, an organisation categorised as industry.
Muse Spark— when was it released?
It was published in April 2026.
Muse Spark— what is it used for?
It works in the domain of Multimodal, Language, Vision, and is recorded as handling the task of language modeling/generation, Question answering. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Muse Spark— 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.
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.