Meta 发布 Muse Wonder 系列模型，主打 Active Memory 与 Active Focus
Meta Unveils Muse Wonder AI Models Featuring Active Memory < IT·Gaming < 기사본문 - The Elec Inc.
Meta 于 10 月 13 日发布前沿模型 Muse Wonder 系列，包含 Muse Wonder 和 Muse Wonder Full 两个版本，均仅通过每月 50 美元或 200 美元的付费订阅提供。Muse Wonder 可通过 SDK 或按量付费 API 供开发者接入，Muse Wonder Full 无对外 API 或 SDK，仅限 Meta 自有环境使用，更适合长周期复杂任务。该系列主打 Active Memory 与 Active Focus 两项能力，前者主动保留历史对话与用户上下文，后者在任务受阻时尝试替代方案。在 Artificial Analysis 评测中，Muse Wonder Full 在 CritPt 科学推理测试和 GDP.pdf 专业文档基准中排名第一，Terminal-Bench 4.0 得分从上一版的 33% 升至 57%；Intelligence Index 上 Muse Wonder 得 52 分、Muse Wonder Full 得 56 分，后者与 Claude Sonnet 5.5 并列第二。AA 称两款模型输出 token 用量比 Muse Spark 少约 10%，Muse Wonder Full 输入 token 比 Muse Wonder 少 16%。Muse Wonder 定价为每百万输入 token 4 美元、每百万输出 token 20 美元。
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Muse Wonder Full ties Anthropic's Claude Sonnet 5.5 in Artificial Analysis rankings
Hyun-Seon, Park; Published 2026.10.13 17:49; Reply 0
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.