I believe right now it’s also valid to ditch NVIDIA given a certain budget. Let’s see what can be done with large unified memory and maybe things will be different by the end of the year.

can’t have both

chat is this socialism

no more fokin ambushes

Let it die. A show this frequent can only end up being boring.

For some weird reason, in my country it’s easier to order a Beelink or a Framework than an HP. They will sell everything else, except what you want to buy.

Remind me of what are the downsides of possibly getting a framework desktop for christmas.

That’s a good point, but it seems that there are several ways to make models fit in smaller memory hardware. But there aren’t many options to compensate for not having the ML data types that allows NVIDIA to be like 8x faster sometimes.

For image generation, you don’t need that much memory. That’s the trade-off, I believe. Get NVIDIA with 16GB VRAM to run Flux and have something like 96GB of RAM for GPT OSS 120b. Or you give up on fast image generation and just do AMD Max+ 395 like you said or Apple Silicon.

I’m aware of it, seems cool. But I don’t think AMD fully supports the ML data types that can be used in diffusion and therefore it’s slower than NVIDIA.

it’s most likely math

Congratulations Nintendo, you played yourself.