Meta releases open-source Muse Glimmer model with 30B parameters

Meta releases open-source Muse Glimmer model with 30B parameters Meta Platforms Inc. today released Muse Glimmer, an open-source language model that can run on personal computers. The company also published a lengthy essay penned by Chief Executive Officer Mark Zuckerberg. The document discusses the risks of artificial intelligence, open-source model regulations and several related topics. Muse Glimmer features 30 billion parameters, which means that it would normally require about 55 gigabytes of RAM. Meta’s engineers shrunk its footprint to under 20 gigabytes using various optimization methods. As a result, it can run on personal computers and Macs with a single consumer-grade graphics card. One of the optimization methods Meta used is called quantization. It compressed each of the model’s weights, the configuration settings that determine how it processes data, into four bits. The company determined that the quantization introduced “minimal to no degradation on agentic tasks.” Muse Glimmer generates prompt responses through a two-step process. First, it uses a less advanced “drafter” model to output an initial answer. It then verifies the accuracy of the drafter’s answer, refines it and delivers the polished response to the user. That approach, which is known as speculative decoding, is faster than having Muse Spark generate prompt responses on its own. Meta trained the model on data generated by its flagship Muse Spark series of proprietary AI models. The company then refined Muse Glimmer through two additional training runs. In the first run, Meta enhanced the model’s ability to tackle lengthy prompts and reasoning tasks. The second training session made Muse Glimmer better at powering AI agents. Some models stop running if they encounter an obstacle while processing a prompt. According to Meta, its engineers trained Muse Glimmer to retry tasks that it fails to complete on the first attempt. Users can adjust how much time and computing power Muse Glimmer spends on each task thanks to built-in “reasoning strength” settings. Meta tested the model across two dozen popular AI benchmarks. According to the company, Muse Glimmer outperformed the comparably-sized Gemma4-31B and Qwen3.6-27B across half the benchmarks. The evaluations in which the model won first place covered tasks such as online research, code generation and scientific chart analysis. The launch of Muse Glimmer comes more than a year after Meta released its last open-source AI model. In today’s essay, Zuckerberg wrote that the company plans to resume releasing open-source models. He wrote that the next AI release will be “soon.” The lengthy document also covers a range of other topics. It contains predictions about the economic benefits of AI, a lengthy discussion of the technology’s risks and suggestions to policymakers. In particular, the essay calls on the U.S. government to reduce regulatory obstacles to open-source model development. According to Zuckerberg, Meta’s board is adopting a governance structure that will enable it to define AI safety criteria. The company will use those criteria to evaluate each of its future models and determine whether they should be broadly released. The essay calls on other frontier AI developers to adopt similar measures. Additionally, Zuckerberg argues that AI labs should give the government access to new models while they’re still being trained. He said such early access would make it easier to address AI-related cybersecurity risks. Image: Meta A message from John Furrier, co-founder of SiliconANGLE: Support our mission to keep content open and free by engaging with theCUBE community. 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