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You'd have to stack 16 of these to get 2TB of VRAM, equivalent to 4 Mac Studios 512GBs chained together. 16 compared to 4. Surely even much faster networking i
by aurareturn 1y ago
You'd have to stack 16 of these to get 2TB of VRAM, equivalent to 4 Mac Studios 512GBs chained together.
16 compared to 4. Surely even much faster networking in the Spark would degrade with that many devices?
Biggest problem with Macs is that they don't have dedicated tensor cores in the GPU which makes prompt processing very slow compared to Nvidia and AMD.
- themgt 1y agon.b. there's been a little speculation that Apple adding TensorOps to Metal 4 suggests M5/M6 may get tensor cores. https://x.com/liuliu/status/1932158994698932505 https://x.com/liuliu/status/1932158994698932505 https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf https://developer.apple.com/metal/Metal-Shading-Language-Spe...
- aurareturn 1y agoNice. I hope so. That would make Macs the best local LLM machines for the masses by far.
- thomasskis 1y agoIt’s $12k for each Mac Studio, and the networking makes them only effective individually (it’s like less that 15 tokens/s with EXO) while NVLINK is very effective. The Spark is definitely more scalable, but the MLX and metal teams are cooking, so honestly either way is still winning.