Meta Launches Muse Spark – New Native Multimodal AI Model
Meta has introduced Muse Spark, its first native multimodal large AI model. The new model offers visual chain-of-thought capabilities and enhanced agent coordination.

What happened?
Meta has launched Muse Spark, the company's first native multimodal large AI model developed by the Meta Superintelligence Labs division. The model has been integrated into the Meta AI App and the web, and has been made available via API in version Muse Spark 1.1. It combines image recognition, code generation, and a so-called 'contemplative mode' for the parallel operation of multiple AI agents.
Key facts
| Artificial Analysis-poäng | 52 poäng (Llama 4: 18 poäng) |
|---|---|
| Multimodal diagramförståelse | 86.4 poäng |
| Hälsofrågor & svar | 42.8 poäng |
| Förträningskapacitet | 1/10 av beräkningsresurserna för Llama 4 |
Why it matters
Muse Spark marks a technical progression from previous Llama models by offering direct visual chain-of-thought capabilities and a significant reduction in the computational capacity required for pre-training. Among other capabilities, the model can convert UI sketches directly into executable HTML, CSS, and JavaScript, as well as analyze complex medical images.
Who is affected?
The launch concerns developers looking to build on Meta's API, as well as consumers using Meta's platforms and the Meta AI App. It is also aimed at businesses seeking cost-effective AI agents for coding and visual data analysis.
Impact on the EU
Muse Spark is being rolled out globally via Meta AI and the Meta AI App. Exact availability and regulatory compliance within the EU depend on Meta's adherence to the EU AI Act and GDPR regarding data collection and the handling of personal data.
What else you should know
The model represents the first significant result from Meta Superintelligence Labs following its restructuring. Performance figures cited are based on initial measurements from Artificial Analysis, although independent reviews are expected to provide a more comprehensive picture of the model's capabilities in comparison to competing systems.
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