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Meta’s Muse Wonder models are designed for more than one-off chat: the company says they can carry context across conversations and persist through multi-step tasks. For developers, Muse Wonder is available through Meta’s API and Muse Code; Muse Wonder Full is offered through eligible Muse Code subscriptions. The announcement does not establish independent performance or safety outcomes, so creators and developers should treat the capabilities as Meta’s claims, not proven guarantees.
What are Muse Wonder and Muse Wonder Full?
Meta announced Muse Wonder and Muse Wonder Full on October 12, 2026, describing them as models for personal and professional agentic work, including coding and tasks involving documents. Meta’s examples include navigating an insurance claim, understanding a lease, and handling personal finance information. These are proposed use cases from Meta, not independently verified results.
The central distinction Meta draws is between ordinary conversational responses and work that can involve context and follow-through. The company describes two features:
- Active Memory: designed to bring useful context forward across conversations.
- Active Focus: designed to keep working toward a goal, recover from errors, try alternatives, and ask for clarification when needed.
These descriptions do not guarantee that a model will remember every relevant detail, complete a task correctly, or know when human intervention is necessary.
#1 Best Overall
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- PCIe & USB 4.0 v2: Up to three PCIe slots can be equipped, including a dual-slot x16 GPU. The main slot supports PCIe 5.0, meeting the needs of high-bandwidth creative and computing workloads. USB 4.0 v2 (80Gbps) supports high-bandwidth external storage and displays.
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- Server-grade thermal architecture: Utilizing a dedicated CPU/GPU airflow design, equipped with a 6-pipe dual-fan cooler, it maintains stable performance even under sustained loads, delivering up to 140W Turbo power while maintaining a 100W TDP, and operating with noise levels as low as 36 dB. An integrated 350W power supply ensures stable and reliable output for demanding computing tasks and fully loaded extended configurations.
How can creators and developers access the models?
The models have different access routes. Meta says Muse Wonder is available through Meta Model API and Muse Code. Muse Wonder Full is available to eligible Muse Code subscribers; Meta’s developer announcement names the Power Usage and Maximum Usage plans. Meta also says Muse Wonder will later power Muse experiences, rolling out first to subscribers. That is a future availability statement, not a claim that the Muse integration is already generally available.
| Model | Access described by Meta | Billing route |
|---|---|---|
| Muse Wonder | Meta Model API and Muse Code | API token pricing is published; Muse Code access is through its subscription service. |
| Muse Wonder Full | Muse Code, for Power Usage and Maximum Usage subscribers | Subscription access; the cited sources do not list separate API token pricing. |
Meta’s model listing gives both models a 1-million-token context window. A large context window may help with lengthy inputs, but it does not by itself demonstrate accuracy, reliable recall, or successful completion of a workflow. Meta’s Muse Wonder model listing is the source for the current context-window and cached-input figures.
What can Muse Wonder do in coding and agent workflows?
Meta says Muse Wonder supports multi-step reasoning, long-running agents, and advanced computer use. Its developer materials describe tool invocation, failure recovery, and coding work in agent scaffolds. In practical terms, these are capabilities intended to let an application give the model tools, allow it to attempt a sequence of actions, and respond when a step fails.
For creators, the same design could be relevant to workflows that involve several documents or repeated tasks. For developers, the API route may suit experiments that need model calls inside an application, while Muse Code provides a subscription-based route. In either case, plan for human review of consequential actions and test the full workflow—including tool errors and ambiguous instructions—before relying on it.
Rank #3
- Professional AI & Creator Workstation: AMD Radeon AI PRO R9700 GPU with 32GB GDDR6 is engineered for AI development, professional content creation, and compute-intensive workloads.
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- Enterprise-Grade Thermal Solution: Vapor chamber heatsink with industrial Honeywell PTM7950 thermal interface material ensures reliable cooling under sustained professional loads.
How much does the Muse Wonder API cost?
Meta announced Muse Wonder API rates of $4 per million input tokens and $20 per million output tokens. The model listing accessed October 13, 2026, also shows $0.20 per million cached input tokens. These are usage-based rates, so actual spend depends on how many input, cached-input, and output tokens a workflow uses. The cited materials do not provide a representative cost for a creator or developer workflow. Muse Wonder Full is listed as subscription-only through Muse Code, with no separate API token rate stated in the cited materials. Prices and availability can change; check Meta’s developer announcement and the model listing for current details.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is established about performance and safety?
Meta characterizes the models as frontier systems and says they are trained with safeguards related to privacy, harmful use, and defensive cybersecurity. In its October 12 announcement, Meta said the models were trained to avoid sharing private information without permission, turn down requests to assist with harmful acts, and help strengthen defenses against cyberattacks. This states Meta’s training goals; it is not independent evidence of real-world safety outcomes.
Rank #4
- FAST RUNS IN THE FAMILY — The 16-inch MacBook Pro with the M5 Pro or M5 Max chip brings next-generation speed and powerful on-device AI to personal, professional, and creative tasks. With all-day battery life, double the starting storage,* and a breathtaking Liquid Retina XDR display, it’s pro in every way.*
- BUCKLE UP — Along with a next-generation CPU, faster unified memory, and up to 2x faster SSD storage,* M5 Pro and M5 Max feature a more powerful GPU with a Neural Accelerator built into each core, delivering faster AI performance and on-device training capabilities. So you can blaze through demanding workloads at mind-bending speeds.
- BUILT FOR AI — Apple silicon, and every major component that powers it, is designed to run demanding on-device AI workloads like LLM inference and training. And Apple Intelligence helps you write, express yourself, and get things done effortlessly with groundbreaking privacy protections at every step.*
- ALL-DAY BATTERY LIFE — MacBook Pro delivers the same exceptional performance whether it’s running on battery or plugged in.*
- MACOS RUNS APPS FAST — All your go-to apps run lightning fast in macOS, including built-in apps like FaceTime and Messages. Plus, built-in virus protection and free software updates help keep your Mac running smoothly and securely.
Meta says it releases its most capable models under its Superintelligence Scaling Framework and that a fuller safety report with additional evaluations will be available soon. The announcement gives no publication date for that report. The available official material does not establish independent benchmark performance, comparative superiority, creator productivity gains, or developer outcomes. Meta and its developer pages use benchmark and “state-of-the-art” language, but the cited material does not provide enough methodology or independent results to support a ranking.
Quick Recap
Best Value
- 【High-Performance APU】The MS-S1 MAX features an AMD Ryzen AI Max+ 395 APU, integrating a Zen 5 architecture CPU (up to 5.1GHz, 16C/32T, 64M L3 Cache), an RDNA 3.5 GPU, and an NPU (50 TOPS). The total system output is 126 TOPS. It provides powerful parallel computing capabilities for demanding AI workflows. It is ideal for running local LLMs, multimodal models, and computationally intensive tasks
- 【128GB UMA Memory】Equipped with up to 128GB of LPDDR5x-8000MT/s unified memory, it enables the CPU and GPU to access a shared, high-bandwidth memory pool with extremely low latency. Ideal for large-scale AI inference, 3D workloads, and complex timelines in video editing. It eliminates traditional VRAM bottlenecks, ensuring smoother data transfer during high-intensity computations. The UMA design maximizes performance stability under high loads
- 【Flexible Expansion】The MS-S1 MAX features USB4 V2 (up to 80Gbps), dual 10GbE LAN, HDMI 2.1 (up to 8K60), a full-length PCIe x16 expansion slot, and dual M.2 slots supporting up to 16TB RAID 0/1. Wi-Fi 7 provides stronger signal coverage and a more stable wireless experience. The slide-out design facilitates upgrades and maintenance. It easily adapts to personal, studio, or rack-mount enterprise environments
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What should creators and developers weigh before trying them?
- Choose access by workflow: use the API route if you need to integrate Muse Wonder into a product; use Muse Code if its subscription access fits your work. Muse Wonder Full access is tied to the specified subscription plans.
- Estimate API usage: distinguish input, cached input, and output token volume rather than treating the per-million rates as a fixed project cost.
- Test persistence rather than assuming it: evaluate what context carries across conversations, how the model behaves after a failed action, and when it asks for clarification.
- Keep safeguards in your own system: review permissions and outputs, especially where workflows touch personal information, finances, legal documents, or computer actions.
- Separate vendor claims from evidence: the announcement outlines intended capabilities and safeguards, but independent comparative results are not established in the cited material.
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