Meta releases its first frontier model, Muse Wonder
Quick Look
- Meta unveiled Muse Wonder and Muse Wonder Full, its first frontier AI models, claiming performance comparable to Fable 5.1 and GPT-6 Astra.
- Wonder costs $4 per million input and $20 per million output tokens via API, while Wonder Full is restricted to Muse Code subscribers.
- Both emphasize 'active memory' for long-term user context retention, scoring higher on MemoryBench than competitors.
AI-generated summary
Why It Matters
Meta previously released the lightweight Muse Spark model and Muse agent after restructuring its AI efforts under Scale AI founder Alexandr Wang in August of the prior year. The company had avoided state-of-the-art model releases compared to competitors like OpenAI and Anthropic.
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.
Where Muse Spark aimed to be a lightweight model that could perform at low latency, the Wonder models are larger and said to be more capable, with higher benchmark scores and better results on complex tasks like 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.
That scale is reflected in the pricing: 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.
Notably, 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.
In keeping with Meta’s interest in developing personal assistants that can perform tasks over a long period, the company placed particular emphasis on the new models’ ability to retain and synthesize information given by the user, a property Meta calls “active memory.”
To achieve better recall, Meta highlighted the MemoryBench benchmark, which challenges continual learning and memory construction frameworks. According to the company’s testing, Muse Wonder now scores higher on MemoryBench 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 new models are the first frontier model release since Scale AI founder Alexandr Wang restructured Meta’s AI efforts in August of last year. Since then, Meta has released its lightweight Muse Spark model and Muse agent, but has avoided the kind of state-of-the-art model releases OpenAI and Anthropic are known for.
What to Watch
AI outlook — possibilities, not facts
Meta will expand access to Wonder Full beyond Muse Code subscribers within 3-6 months
Likely · Within months
Competitors will announce memory-focused model updates in response to Meta's active memory emphasis
Possible · Within months
Open Questions
- When will Wonder Full be available beyond Muse Code subscribers?
- What specific benchmarks were used to compare Wonder and Wonder Full to Fable 5.1 and GPT-6 Astra?
- How does the pricing of Wonder Full compare to API-accessible models if it were to be offered?
- What safeguards are in place for the 'active memory' feature to prevent data privacy issues?







