Meta released Muse Spark Open today, an open-weight agent model with 816B parameters (42B active), a 1M-token context, and text, image, video and audio in. Their 4-bit NVFP4 weights are about 537GB and the full BF16 is about 1.65TB. Meta serves it on four or eight B300s. I really appreciate Meta opening the weights so we can run it locally, but come on, the marketing is BS. Their announcement calls two Mac Studios with 512GB of RAM each “the best way to run a powerful model on your own desktop”, two machines that “behave like one supercomputer with a terabyte of unified memory”. How many of us actually have, or can afford, that? The 512GB Mac Studio isn’t even on sale yet (late October) and there’s no price for it. The setup you can buy today is four 256GB Mac Studios at about $38k. Every other setup that runs it at a decent quant will cost you tens of thousands at least, so it looks like another model you’ll have to pay an API for, or rent some GPUs to run. Again, nice gesture on the open weights, but I think the marketing is misleading. Meta’s announcement: https://research.meta.ai/blog/muse-spark-open I wrote a blog post about it, with what it takes to run it on Macs, mini PCs, RTX 5090s or a CPU server and what each costs, here: https://www.anchorterminal.com/blog/run-muse-spark-open-locally submitted by /u/ZeroCool86
Originally posted by u/ZeroCool86 on r/ArtificialInteligence