Meta's Superintelligence Lab released two new frontier models on Monday, Muse Wonder and Muse Wonder Full, marking the company's first entry into the high-capability AI model category.
The Wonder models are larger and more capable than Meta's previous Muse Spark lightweight model. According to Meta's testing presented in the model card, Wonder and Wonder Full achieve benchmark scores comparable to Fable 5.1 and GPT-6 Astra. Meta describes the release as "the next step on our scaling ladder and a major leap toward personal superintelligence."
Wonder will be available through the Meta Model API at $4 per million input tokens and $20 per million output tokens, pricing roughly equivalent 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 power the Muse agent.
Meta emphasized the new models' ability to retain and synthesize user information over extended periods, a capability the company calls "active memory." Research scientist Kavya Kopparapu said in an accompanying video: "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."
Meta highlighted the MemoryBench benchmark as a measure of continual learning and memory construction. According to the company's testing, Muse Wonder scores higher on MemoryBench than Fable, Opus, or Astra.
This release represents Meta's first frontier model since Scale AI founder Alexandr Wang restructured the company's AI efforts in August of last year. Since that restructuring, Meta released the lightweight Muse Spark model and the Muse agent but had avoided state-of-the-art model releases comparable to those from OpenAI and Anthropic.
Meta trained the new models at its Prometheus data center in central Ohio, which came online earlier this year.