Meta's Superintelligence Lab released a pair of new state-of-the-art models on Monday, Muse Wonder and Muse Wonder Full, representing the company's first attempt at a frontier model.
The Wonder models are larger and said to be more capable than the earlier lightweight Muse Spark, with higher benchmark scores and better results on complex tasks such as coding. According to Meta's testing, presented in the model card, Wonder and Wonder Full achieve comparable benchmark scores to Fable 5.1 and GPT-6 Astra.
"Together, they mark the next step on our scaling ladder and a major leap toward personal superintelligence," Meta's blog post about the models reads.
Accessed through the Meta Model API, Wonder will cost $4.00 per million input tokens and $20.00 per million output tokens, making it roughly equivalent in cost to GPT-6 Sol or Opus 5.5. Wonder Full will only be available to Muse Code subscribers and will not be served through the API. Both models will also be used to power the Muse agent.
Meta placed particular emphasis on the models' ability to retain and synthesise information given by the user, a property it calls "active memory." According to the company's testing, Muse Wonder now scores higher on the MemoryBench benchmark than Fable, Opus or Astra. "We put a tremendous amount of effort into making sure your model can remember what's important to you over days, weeks, months and beyond," said research scientist Kavya Kopparapu in a video accompanying the launch.
The release is the first frontier model since Scale AI founder Alexandr Wang restructured Meta's AI efforts in August of last year. According to the post, the models were trained at Meta's Prometheus data center in central Ohio, which came online earlier this year.