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Comment by LoganDark | Hacker News Reader

Cool. Where can I buy one?

If I go to the page for the W7900, I can download the datasheet. I can look at the marketing pages. I can look at the specifications and download drivers. But I can't buy the card.

If I look for one on eBay, they start at $4600, which is still far too expensive for 48GB. At that point, just buy an Apple Silicon machine and you can get far more memory than that for even cheaper. (M3 Max MacBook Pro with 96GB memory is just $4,000!)

Alright, let's try the RTX A6000! Oop, it's $4,000. Cheaper than AMD, but wow! Oh, and I can only find these prices on eBay, you can't buy them direct from Nvidia as a consumer.

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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?

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

Interesting, i didn't know this existed.

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.

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?

> 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.

> 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

> 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.

NVidia primarily doesn't sale to consumers. You'll have to get from 3rd-party like PNY. It is costly because they have customers lining up to pay that price. If demand goes down price will follow.

And same applies to AMD. A reputable retailer selling W7900s: https://www.bhphotovideo.com/c/product/1765536-REG/amd_100_3...

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