Apple markets a four-Mac cluster for trillion-parameter local inference
- Source
- x.com
- Date
Apple's marketing video posted by Joz, includes the 4 x M5 Ultra clustered solution. The cluster has 2TB unified memory @ 4.8TB/s. "Run trillion parameter frontier models locally" https://t.co/qqmXMr3H4X
Clustering has also featured on Apple’s mac studio and mac mini product pages. https://t.co/rKRTIAqKZQ
Context
Alex Cheema's post describes an Apple marketing video that shows four M5 Ultra Macs clustered, with 2TB of unified memory at 4.8TB/s, under the line "Run trillion parameter frontier models locally." Those totals are aggregates. Apple's Mac Studio specifications list up to 512GB of unified memory and 1.2TB/s of memory bandwidth per machine, and four machines multiply out to roughly 2TB and 4.8TB/s.
That arithmetic accounts for the totals but does not measure how quickly one model runs across the machines. The bandwidth sum describes memory access inside each computer, not the speed of the connections between them, so it is not a single shared pool. A trillion-parameter model's actual performance needs a specified model configuration and a cluster , which the post does not report.
- benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
- postIs the Rush to Build New LLM Inference Engines Fragmenting the Ecosystem?
- postBig model. 2.4T params, 95B active. 4.89TB. Surprised they didn't release a 4-bi
post@Jason @Lons @eisokant @ape Correction: Should actually be closer to 50 tok/sec
postLocal inference crosses over: the M5 Ultra and the 1,000x claim
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