3 ms·

Just checking here but are you comparing a macbook with 96GB of machine RAM to a GPU with 48GB of on-card RAM? Because if so you can get a good pc with 96GB of

Just checking here but are you comparing a macbook with 96GB of machine RAM to a GPU with 48GB of on-card RAM? Because if so you can get a good pc with 96GB of machine ram for significantly less than $4000. Unless the claim is that an M3 Max MacBook has equivalent GPU type compute power as a dedicated GPU?

o_x 3y ago
It's probably because of the unified memory model - the GPU on the macbook can access the memory as if it was dedicated.
- NilMostChill 3y ago
  Interesting, i didn't know this existed.
LoganDark 3y ago
I'm comparing the cost of a GPU with 48GB VRAM to the cost of an Apple Silicon machine with at least 48GB of Unified Memory, yes. (The ASi machine having 96GB of memory instead is just because it's still cheaper than the card, so why not.) A normal PC with 96GB of regular RAM wouldn't allow you to use that RAM for GPU workloads, at least not with a dedicated GPU.
- NilMostChill 3y ago
  As stated above, i didn't know this existed. Would an ASi machine and Dedicated GPU with the same amount of respective RAM have the same performance compute-wise?
  - LoganDark 3y ago
    > As stated above, i didn't know this existed. My comment was made 10 hours before that reply, so I didn't have that context. Sorry. > Would an ASi machine and Dedicated GPU with the same amount of respective RAM have the same performance compute-wise? Not sure, but performance comes after making sure you have enough VRAM to run your workload in the first place. I doubt an ASi chip would beat most datacenter-class training cards, but if a consumer just wants to train a model locally without much regard for getting the best possible performance, there is more value-for-money.
    - NilMostChill 3y ago
      > My comment was made 10 hours before that reply, so I didn't have that context. Sorry. Sorry, i phrased that poorly, i was referencing my own comment, not because i thought you had ignored it but because i had just replied to the other comment. It probably shouldn't have reference the other reply. > Not sure, but performance comes after making sure you have enough VRAM to run your workload in the first place. I doubt an ASi chip would beat most datacenter-class training cards, but if a consumer just wants to train a model locally without much regard for getting the best possible performance, there is more value-for-money. That mostly makes sense. Though personally,if i'm dropping car money on hardware to run a model then i'd really want to know the type of difference in power, are we talking about the ASi taking twice as long or are we talking orders of magnitude? Not a question for you specifically, just a thought. I'll see if i can find any benchmarks for the differences in compute. Thanks
      - LoganDark 3y ago
        > are we talking about the ASi taking twice as long or are we talking orders of magnitude? I'm not aware of any benchmarks comparing Apple Silicon to datacenter-class chips, unfortunately.

o_x 3y ago

It's probably because of the unified memory model - the GPU on the macbook can access the memory as if it was dedicated.

NilMostChill 3y ago
Interesting, i didn't know this existed.

LoganDark 3y ago

I'm comparing the cost of a GPU with 48GB VRAM to the cost of an Apple Silicon machine with at least 48GB of Unified Memory, yes. (The ASi machine having 96GB of memory instead is just because it's still cheaper than the card, so why not.) A normal PC with 96GB of regular RAM wouldn't allow you to use that RAM for GPU workloads, at least not with a dedicated GPU.

NilMostChill 3y ago
As stated above, i didn't know this existed. Would an ASi machine and Dedicated GPU with the same amount of respective RAM have the same performance compute-wise?
- LoganDark 3y ago
  > As stated above, i didn't know this existed. My comment was made 10 hours before that reply, so I didn't have that context. Sorry. > Would an ASi machine and Dedicated GPU with the same amount of respective RAM have the same performance compute-wise? Not sure, but performance comes after making sure you have enough VRAM to run your workload in the first place. I doubt an ASi chip would beat most datacenter-class training cards, but if a consumer just wants to train a model locally without much regard for getting the best possible performance, there is more value-for-money.
  - NilMostChill 3y ago
    > My comment was made 10 hours before that reply, so I didn't have that context. Sorry. Sorry, i phrased that poorly, i was referencing my own comment, not because i thought you had ignored it but because i had just replied to the other comment. It probably shouldn't have reference the other reply. > Not sure, but performance comes after making sure you have enough VRAM to run your workload in the first place. I doubt an ASi chip would beat most datacenter-class training cards, but if a consumer just wants to train a model locally without much regard for getting the best possible performance, there is more value-for-money. That mostly makes sense. Though personally,if i'm dropping car money on hardware to run a model then i'd really want to know the type of difference in power, are we talking about the ASi taking twice as long or are we talking orders of magnitude? Not a question for you specifically, just a thought. I'll see if i can find any benchmarks for the differences in compute. Thanks
    - LoganDark 3y ago
      > are we talking about the ASi taking twice as long or are we talking orders of magnitude? I'm not aware of any benchmarks comparing Apple Silicon to datacenter-class chips, unfortunately.