Meta releases Muse Wonder, the models Zuckerberg says bring it to the frontier
Meta built them to remember you between chats and push through hard tasks, but its full safety report isn't out yet.
On October 12, 2026, Meta released Muse Wonder and Muse Wonder Full, which its newsroom post calls its most capable models to date. Developers can use Muse Wonder now through the Meta Model API and Muse Code. Muse Wonder Full is only open to Muse Code subscribers.
Mark Zuckerberg announced the pair on X at 12:55 pm Eastern.
Introducing Muse Wonder, our new family of frontier models with state of the art performance for personal and professional agentic work.
- Released
- October 12, 2026
- Muse Wonder pricing
- $4 input, $20 output per 1M tokens
- Context window
- 1M tokens
- Intelligence Index
- 56 for Muse Wonder Full, 52 for Muse Wonder
- Safety report
- will be available soon
What Meta says they do
Meta built both for agents, software that carries out tasks for you instead of only answering. Its research post names two features. Active Memory is the first. Active Focus is the second, and it's meant to keep the model going when a job gets hard.
The examples Meta gives are everyday chores: an insurance claim, a lease, someone's finances, a working app. It trained both models at Prometheus, its gigawatt-scale data center, and plans to use Muse Wonder to build specialized models "we can bring to everyone using Muse."
The research post makes a case for breadth over benchmark scores, which is a fair thing to want from a model that's meant to run errands nobody planned for.
Two models often have similar benchmark scores, yet one seems to handle a much wider range of unfamiliar tasks.
In a second post, Zuckerberg tied the release to the lab Meta set up a little over a year ago.
It's been just over a year since we started Meta Superintelligence Labs. Muse Spark was our first family of models, and now Muse Wonder is a much larger and more advanced class of models that brings us to the frontier. We're releasing two models today. Muse Wonder for fast frontier performance and Muse Wonder Full for the full version of the model.
What an outside test found
Meta's own scores sit in charts on its research blog, and I couldn't read them as text, so the numbers here come from Artificial Analysis. It posted results 30 minutes after Zuckerberg did, and it also worked out what a task costs to run, which Meta's posts don't.
Meta has released Muse Wonder and Muse Wonder Full, achieving Artificial Analysis Intelligence Index v4.3 scores of 52 and 56 at max reasoning effort - each a material gain over Muse Spark 1.3 (max) at 48, with a release gap of only 6 weeks Muse Wonder is available for users on Meta’s first-party API, while Muse Wonder Full is currently only available for Muse Code users. Meta notes that each model is designed for personal and professional agent use Congratulations to @AIatMeta, @finkd, and @alexandr_wang on the release! Key Takeaways: ➤ Both models exhibit a material jump in overall Intelligence Index score. Muse Wonder Full (max) improves on Muse Spark 1.3 (max) across all ten Intelligence Index evaluations, gaining 8 points to 56. The largest gains were seen in agentic evaluations: Terminal-Bench 4.0 (+24 points, 33% to 57%), GDPval-AA v2.1 (+176 Elo, 1681 to 1857), and AA-Briefcase (+148 Elo, 1581 to 1729). Muse Wonder (max) gains 4 Intelligence Index points and lands at 52, with notable improvements vs. Muse Spark 1.3 (max) in Terminal-Bench 4.0 (33% to 52%) and AutomationBench-AA (58% to 68%) ➤ Muse Wonder Full (max) places in the top three on six of the ten Intelligence Index evaluations, and is particularly strong in agentic knowledge work and scientific reasoning. In agentic knowledge work, it narrowly leads on GDP.pdf (33%), ranks #2 on GDPval-AA v2.1 (1857 Elo), and #3 on both AA-Briefcase (1729 Elo) and AutomationBench-AA (71%). In scientific reasoning, it tops the CritPt leaderboard at 33% and ranks #3 on SciCode with 63%. This builds on the relative strengths of Muse Spark 1.3 (max), which also showed particular ability in these two domains ➤ Both models use fewer output tokens than Muse Spark 1.3 (max). Muse Wonder (max) and Muse Wonder Full (max) each use around 54k output tokens per Intelligence Index task, down ~10% from Muse Spark 1.3 (max, 60k). This usage is lower than similarly intelligent models Gemini 4 Argon (high, 62k) and Claude Fable 5.1 (max w/ fallback, 78k), but higher than GPT-6.1 Sol (max, 38k) and GPT-6 Astra (max, 27k). Muse Wonder Full (max) uses 16% fewer input tokens per Intelligence Index task than Muse Wonder (max) (6.44M vs 7.69M), meaning it is both more intelligent and more token-efficient ➤ Cost per Task for Muse Wonder (max) lands higher than most similarly intelligent models. Despite efficient output token use, premium API pricing ($4 per million input tokens, $20 per million output tokens) and high input token use (7.69M per task) push Muse Wonder (max)’s cost to $4.52 per Intelligence Index task. This is lower than Claude Fable 5.1 (max w/ fallback, $7.63), Claude Opus 5.5 (max w/ fallback, $5.98), and Claude Sonnet 5.5 (max w/ fallback, $5.46), but higher than GPT-6 Astra (max, $3.26), Gemini 4 Argon (high, $1.99), GPT-6.1 Sol (max, $0.72), and its predecessor Muse Spark 1.3 (max, $1.60). Per-token pricing is not currently available for Muse Wonder Full, so no Cost per Task figure can be estimated at this stage ➤ Both models gain significantly in Coding Agent performance. Muse Wonder Full achieves 68 on the Artificial Analysis Coding Agents Index at max effort in Muse Code, alongside Claude Code with Sonnet 5.5 (max, 68) and Opus 5.5 (max, 66). Muse Wonder (max) scores 63. These represent material gains over Muse Code with Muse Spark 1.3 (max), which scores 54 Other details for the two new models: ➤ Context windows: 1M tokens each, unchanged from Muse Spark 1.3 ➤ Pricing: for Muse Wonder, $4 input / $0.20 cached input / $20 output per 1M tokens. Pricing per token is not yet announced for Muse Wonder Full ➤ Input modalities: text, image, video, and audio ➤ Output modalities: text ➤ Availability: Muse Wonder is available on Meta's first-party API and Muse Code at launch, while Muse Wonder Full is only available to Muse Code users
Cost is where Muse Wonder looks weaker. At $4 per million input tokens and $20 per million output, Artificial Analysis puts one task from its index at $4.52. That's cheaper than Claude Opus 5.5 at $5.98, but it's more than six times GPT-6.1 Sol's $0.72. Muse Wonder Full has no per-token price yet.
The safety report comes later
Meta says it trained the family to avoid sharing private information without permission and to turn down requests to help with harmful acts. It calls Muse Wonder "our most aligned model to date" and says it releases models under its Meta Superintelligence Scaling Framework.
The evidence for that isn't public yet. Meta's newsroom post says a full report with more safety evaluations "will be available soon," and gives no date. Muse Wonder will also start powering the Muse agent app, with subscribers first.
More on Meta
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- Meta open-sources Muse Gadgets, so you can build hardware for its AI agentOctober 3, 2026
- Meta starts an enterprise AI unit and hires MongoDB's CEO to run itSeptember 29, 2026
- Meta's Muse agent is coming to its glasses and will act on what you're looking atSeptember 24, 2026