Meta thinks the next front in the AI race may be sitting on your desk.
On Aug. 10, Meta released Muse Glimmer, a 30-billion-parameter AI model designed to run locally on a Mac or PC with a single consumer GPU. Its weights are available to download from Hugging Face under a permissive Apache 2.0 license, allowing developers to use, modify, and build products with the model for free.
That means Muse Glimmer can operate without sending every request to a distant data center. It can also work without an internet connection, provided the computer running it has enough memory and processing power.
For anyone ready to open an app and start chatting, however, there is a catch: Muse Glimmer is a developer release. Meta is supplying the model that can power an AI agent, rather than a consumer product that immediately manages your inbox or reorganizes your desktop.
What can Muse Glimmer actually do?
Meta built Muse Glimmer for “agentic” work, meaning it can take a goal, divide it into steps, and use connected tools to complete parts of the task. The company imagines local agents that could manage schedules, draft messages, organize files, and write or debug code.
The model can process images alongside text, perform multi-step tasks, and attempt recovery when a tool fails. Meta says it was trained on data from more than 100 languages.
Fitting those abilities onto one computer required some downsizing. At full precision, Muse Glimmer would need more than 55 GB of memory. Meta compressed the model to below 20 GB, leaving additional room for its working memory and image-processing system.
Even so, “runs on your laptop” is doing some work here. Meta designed the compressed version to fit within a 24 GB or 32 GB memory envelope and tested it on hardware, including Apple’s M4 Max and M5 Max chips and Nvidia’s RTX 5090. Your average work laptop may sit this one out.
Mashable Light Speed
For people with the right hardware, local processing offers some clear advantages. The model can work offline, developers can avoid paying for every request to a cloud service, and personal information does not necessarily have to leave the device. The level of privacy will still depend on how each application is built and which outside services it can access.
In Meta’s own benchmark tests, Muse Glimmer performed competitively against similarly sized models from Google and Alibaba, although those results have not yet been independently verified.
Zuckerberg takes aim at closed AI
Meta describes Muse Glimmer as open source, although “open weight” is the more precise term. The calculations the model learned during training are public, but the release does not expose all the data and infrastructure used to create it.
Still, the Apache 2.0 license gives developers considerably more freedom than they receive from closed models available only through a company’s app or paid API.
Muse Glimmer is also the smaller opening act. Mark Zuckerberg said Meta will soon release the weights for Muse Spark 1.2, its more powerful foundation model. Muse Glimmer was distilled from Spark, meaning it was trained partly by learning from the larger model’s outputs.
Zuckerberg expanded his case for open AI in an essay titled “The Future Is for Everyone.” He argued that the United States should loosen restrictions around training data and distillation so American companies can better compete with open models from Chinese developers, including DeepSeek, Alibaba, and Moonshot AI.
He also took a thinly veiled swipe at companies that warn about AI’s dangers while keeping their most capable models under tight control.
“The notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic,” Zuckerberg wrote.
He did not name OpenAI or Anthropic, but the contrast was clear. Both companies keep their leading model weights private, while their executives have repeatedly warned about the economic and societal risks of more powerful AI. Zuckerberg instead argued that advanced AI should be widely distributed, with each person eventually controlling an agent that understands their goals and personal context.
Releasing Muse Glimmer gives developers another option outside the paid APIs of Meta’s rivals. It also gives Meta a way to influence the AI market even when people are not using one of its apps.
Whether ordinary users are ready to give a local agent access to their schedules, messages, and files remains an open question. The more immediate hurdle may be finding a laptop muscular enough to run it.
Topics
Artificial Intelligence
Meta
