Meta 發佈 Muse Wonder 系列 AI 模型，主打 Active Memory 與 Active Focus

Meta Platforms announced Oct. 13 that it has unveiled its latest frontier artificial intelligence (AI) models, the Muse Wonder series, featuring major improvements in AI agents' ability to independently handle complex tasks.

​The series comprises two versions, Muse Wonder and Muse Wonder Full. The models are differentiated by their availability to external developers and their use within Meta's proprietary work environment. Both are available only through paid subscriptions priced at $50 or $200 a month.

​Muse Wonder can be accessed directly by developers through a software development kit (SDK) or a pay-as-you-go application programming interface (API), allowing them to integrate the model into applications or customize it for various workflows. Muse Wonder Full, by contrast, has no standalone API or SDK for external access and is restricted to Meta's dedicated environment. It is also better suited to long-horizon tasks involving complex, extended sequences of work.

​Meta's decision to separate its high-performance AI models into versions for external developers and its own services is notable. The strategy appears designed to generate revenue from direct model sales while strengthening its proprietary AI productivity tools. Meta is seeking to expand its monetization opportunities in the enterprise AI market, where it competes with OpenAI, Anthropic PBC, and Google LLC. The company has until now focused on expanding its ecosystem through Llama, its open AI model family.

​The standout features of the Muse Wonder series are Active Memory and Active Focus. Active Memory proactively retains information from previous conversations and important user context, retrieving it when needed to maintain continuity across tasks. Active Focus attempts alternative approaches when obstacles arise during challenging assignments, helping the model complete tasks and achieve its objectives.

​Muse Wonder Full received strong marks for task performance in benchmarks from Artificial Analysis (AA), an independent AI evaluation organization. It ranked first in CritPt, a scientific reasoning test, and GDP.pdf, a benchmark for professional document work. Its Terminal-Bench 4.0 score also rose sharply to 57% from 33% for the previous version.

On AA's Intelligence Index, which measures overall model intelligence, Muse Wonder scored 52 and Muse Wonder Full scored 56 at the highest reasoning setting. Muse Wonder's score of 52 puts it near Google's recently released Gemini 4 Argon, which scored 53, and OpenAI's GPT-6.1 Sol. Muse Wonder Full, with a score of 56, tied Anthropic's Claude Sonnet 5.5 for second place at the time of the evaluation.

The scores also marked a substantial improvement from the 48 recorded by the previous Muse Spark 1.3 model at the maximum reasoning setting, released six weeks earlier.

​AA said both of Meta's latest models use about 10% fewer output tokens than Muse Spark. Muse Wonder Full also uses 16% fewer input tokens than Muse Wonder, making it "smarter and more efficient," according to the evaluator. Muse Wonder is priced at $4 per million input tokens and $20 per million output tokens, putting it at the higher end of the market.

Meta said both models were developed through pretraining and reinforcement learning at its gigawatt-scale Prometheus data center. The company said they achieved state-of-the-art (SOTA) performance across key AI agent benchmarks, including coding, execution of complex long-horizon tasks, and memory management.

​Meta also highlighted safety measures incorporated into its latest AI models. The company said it had strengthened defenses against adversarial prompt attacks and implemented safeguards to prevent misuse involving cyberattacks and chemical, biological, radiological, and nuclear (CBRN) threats.