With new open models, Meta pitches another reboot of its struggling AI strategy

Meta announced it will focus on open-weight large language models, releasing Muse Glimmer, a 30 billion parameter model with a 128,000-token context window, under the Apache 2.0 license, and promising to open the weights for Muse Spark 1.2 in the coming weeks. CEO Mark Zuckerberg published a 6,000-word essay outlining the company's AI philosophy, differentiating Meta from proprietary model developers like OpenAI and Anthropic. The move reflects a growing trend toward local inference to reduce reliance on big AI labs.

Meta has announced its intention to focus on open-weight large language models. Additionally, the company announced the release of an open model called Muse Glimmer and a promise to open the weights for Muse Spark 1.2, its more powerful model, in the next few weeks. Alongside these announcements, Meta CEO Mark Zuckerberg published a more than 6,000-word essay https://about.fb.com/news/2026/08/the-future-is-for-everyone/ outlining the company’s philosophy about AI systems and governance moving forward. The essay aims to differentiate Meta from companies like OpenAI and Anthropic, which develop proprietary models and which have lobbied the US government for help competing against large-scale distillation—which involves using an existing model to train a new one—or open-weight models by Chinese labs. Muse Glimmer https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model is a 30 billion parameter model with a 128,000-token context window by default. It is distilled from Muse Spark, the larger and more capable model that Meta launched earlier this year. Glimmer is meant to run on users’ local machines, rather than via a cloud service or an API. Glimmer’s weights are open source under the Apache 2.0 license. Muse Spark https://developer.meta.com/ai/resources/blog/build-with-muse-code/ was introduced in April as a closed, proprietary, frontier-class model—Meta’s first major model release after a significant shake-up of the company’s AI teams last year, and a departure from its focus on models that are, by some definition, open. When Meta released Muse Spark 1.1 in July, it introduced its first paid service—again, a departure from its previous strategy. Muse Spark 1.2 was released on August 5 and was accompanied by Muse Code, a terminal coding agent. Developers have generally found https://thenewstack.io/meta-muse-claude-code/ that Muse Code doesn’t quite match the frontier models from Anthropic or OpenAI in capability, but it competes well on cost—meaning it has similar positioning to many open-weight models from Chinese labs. As a smaller model designed to run on consumer GPUs, Muse Glimmer won’t compete on that level at all—but it reflects a growing movement to bring some inference to local devices to reduce reliance and spending on the models produced by the big labs like Anthropic and OpenAI.