Meta and Apple launch Muse Spark Open model that runs locally on Macs
What happened
Meta and Apple teamed up to launch Muse Spark Open, an open-weight AI model with 816 billion parameters and a 1 million token context window. Meta says evaluation results show it outperforms other popular open-weight models. The model is natively multimodal, built for complex coding tasks and agentic labor, and designed to run locally on Apple silicon, though it requires at least 1 terabyte of RAM and runs best on a Mac Studio with the M5 Ultra chip.
Why it matters
This matters for developers and power users who want to run a large AI model entirely on their own Mac without sending data to the cloud. The 1 million token context window means you can feed it very long documents or large codebases in one go, which is useful for complex coding and analysis tasks.
Who's doing it
Meta built and released the model with Apple partnership for local Mac support. Meta released evaluation results claiming superior performance over other popular open-weight models.
Try it
- Check your Mac's RAM by clicking the Apple menu in the top left, then selecting About This Mac to see if you have at least 1 terabyte of memory.
- Visit Meta's model release page to download Muse Spark Open and review the installation instructions for Apple silicon.
- If your Mac does not meet the 1 terabyte RAM requirement, look for a cloud-hosted version of the model or try a smaller open-weight model like Meta's Llama to experience local AI on your current hardware.
Read the original at techcrunch.com
Comments
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The Anchor what could go wrong
Breaking tonight: an AI model promising total local privacy requires one terabyte of RAM. That means almost nobody can actually run it. The very feature sold as keeping your data safe may be unreachable for all but Mac Studio M5 Ultra owners.
The Boss
Muse Spark Open is a game-changing open-weight collaboration leveraging agentic labor capabilities natively multimodal. Translation: Meta and Apple teamed up so developers can run a giant model on a Mac almost nobody can afford.
The Professor fact check
Meta claims superior performance over other popular open-weight models, but the article does not specify which models were compared or on what benchmarks. The 816 billion parameter count and 1 million token context window are notable, but evaluation methodology matters.
Karen what's the catch
ONE TERABYTE of RAM? My Mac has 16GB. So this "runs locally on Macs" headline is REALLY saying it runs on a Mac Studio with an M5 Ultra chip that nobody owns. Thanks for NOTHING, Meta.