4 ms·

Let's see Nvidia's transistor count.

• alecco 3y ago
  It's apples to oranges but here we go: M2 134bn 192GB RAM 800GB/s 3 TFlops? $9,600 H100 80bn 188GB VRAM 900GB/s 60 TFlops $40,000 A100 54bn 80GB VRAM 600GB/s 20 TFlops $10,000 4090 76bn 24GB VRAM 1000GB/s 82 TFlops $1,400 [1] https://www.nvidia.com/en-us/data-center/h100/ https://www.nvidia.com/en-us/data-center/h100/ [2] https://en.wikipedia.org/wiki/Ampere_(microarchitecture)#A100_accelerator_and_DGX_A100 https://en.wikipedia.org/wiki/Ampere_(microarchitecture)#A10... [3] https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_proces...
  • skunkworker 3y ago
    M2 Ultra on a Mac Studio with 192gb is $5599 (60 core gpu), or $6599 (76 core gpu).
    • kaliqt 3y ago
      I really want to see how that fares against Nvidia for ML development, because it's hard to compete with that kind of flexibility and price.
    • alecco 3y ago
      H100 has 16k cores, but of course that's a completely different kind of core.
  • alecco 3y ago
    Somebody please correct why 4090 looks so close to H100, it looks off.
  • deleted 3y ago
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  • shpx 3y ago
    Cerebras's Wafer Scale Engine Two (WSE-2) has 2.6 trillion transistors. https://en.wikipedia.org/wiki/Cerebras https://en.wikipedia.org/wiki/Cerebras https://www.anandtech.com/show/16626/cerebras-unveils-wafer-scale-engine-two-wse2-26-trillion-transistors-100-yield https://www.anandtech.com/show/16626/cerebras-unveils-wafer-...
• deleted 3y ago
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