Morning Edition · Wednesday, September 9, 2026Published at 2:20 AM EDT · New York
The agent runs in isolated virtual machines, reaches users through WhatsApp, and is built on the Muse Spark model line that scored 88.8 percent on Terminal-Bench 2.1 a week earlier.

Meta launched Muse, a personal agent that books travel, files forms, handles email and shops on a user's behalf, on September 8. Each user's agent runs inside an isolated virtual machine with its own security boundary, the architectural answer to the obvious objection that an agent with credentials and browser access is a standing risk. Access is through a dedicated app and through WhatsApp, the distribution asset no competitor can match.
Pricing is unusually explicit about the underlying cost driver. Meta offers a free tier that Mark Zuckerberg described as usable up to about 100 million tokens a week, plus Power at 20 dollars a month and Maximum at 100 dollars a month, according to reporting on the launch. Metering consumers in tokens rather than messages shows that Meta expects agent sessions, not simple chats.
The model that powers Muse shipped a week earlier. Meta released Muse Spark 1.3 on September 2 into Muse Code and its model application programming interface (API), reporting 75.4 percent on DeepSWE 1.1, 88.8 percent on Terminal-Bench 2.1 and 98.5 percent on long-context retrieval. Those are vendor-reported numbers on agentic and coding suites, and Alexandr Wang, Meta's chief AI officer, told Axios the update was groundwork for personal agents.
What this means
Meta is competing on distribution and price rather than on frontier benchmark leadership, and a free tier measured in tokens is a direct subsidy against per-seat agent products from OpenAI, Anthropic and Google. The exposed group is the consumer agent startup layer, which buys inference at retail and now faces a rival that gives away a weekly token allowance large enough for most personal tasks. The second channel is inference demand: agents that browse, fill forms and retry failures consume far more tokens per user than chat, so Meta's own capital spending on serving capacity rises with adoption rather than falling.
What to watch
Part of a tracked trend
Hyperscalers Enter the Frontier API Market
Large platform companies increasingly convert in-house frontier models into metered, incumbent-compatible APIs, competing on switching cost and distribution rather than pure capability.
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Observations to monitor, not financial advice.
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