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Comment by pclmulqdq | Hacker News Reader

AMD doesn't care about you being able to do computing on their consumer GPUs. The datacenter GPUs have a pretty good software stack and great support.

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I'm inclined to believe it but that difference is exactly how nvidia got so far ahead of them in this space. They've consistently gone out of their way to put their GPGPU hardware and software in the hands of the average student and professional and the results speak for themselves.

Just look at the disaster of rocm or you need to spend 300k on software engineers to get anything so work

I wouldn't say so. Nvidia bet on machine learning a decade or so before AMD got the memo. That was a good bet on Nvidia's part. In 2015 you just had to have an Nvidia card if you wanted to do ML research. Sure, Nvidia did hand them out in some cases, but even if you bought an AMD card it just wouldn't work. It was Nvidia or go home. Even if AMD now did everything right (and they don't), there's a decade+ of momentum in Nvidia's favor.

Yes but then they fail to understand a lot of “long tail” home projects, opensource stuff etc is done on consumer GPUs at home, which is tremendously important for ecosystem support.

Nvidia started removing nvlink with the 4000 series, they aren't heavily focused on it either anymore and want to sell the workstation cards for uses like training models at home.

As a beginner, you can get a lot done on a 4060ti/5060ti 16gb, much less a 4090/5090.

Heck I’ve been able to work through the early chapters of the FastAI book using a lowly Quadro p1000

What if they understand that and they don't care? Getting one hyperscaler as a customer is worth more than the entire long tail.

Then they’re fools. Every AI maestro knows CUDA because they learned it at home.

It’s the same reason there’s orders of magnitude more code written for Linux than for mainframes.

The problem is that this is short-term thinking. You need students and professionals playing around with your tools at home and/or on their work computers to drive hyperscale demand in the long term.

This is why it’s so important AMD gets their act together quickly, as the benefits of these kind of things are measured in years, not months.

Why would a hyperscaler pick the technology that’s harder to hire for (because there’s no hobbyist-to-expert pipeline)?

Then they will stay irrelevant in the GPU space like they have been so far.

On the corp side you have FB w/ PyTorch, xformers (still pretty iffy on AMD support tbt) and MS w/ DeepSpeed. But let's see about some others:

Flash Attention: academia, 2y behind for AMD support

bitsandbytes: academia, 2y behind for AMD support

Marlin: academia, no AMD support

FlashInfer: acadedmia/startup, no AMD

ThunderKittens: academia, no AMD support

DeepGEMM, DeepEP, FlashMLA: ofc, nothing from China supports AMD

Without the long tail AMD will continue to always be in a position where they have to scramble to try to add second tier support years later themselves, while Nvidia continues to get all the latest and greatest for free.

This is just off the top of my head on the LLM side where I'm focused on, btw. Whenever I look at image/video it's even more grim.

Modular says Max/Mojo will change this and make refactoring between different vendors (and different lines of the same vendor) less of a showstopper but tbd for now

The judge is still out there regarding if Max/Mojo is going to be something that the large majority cares about.

Why should we care about them if they don't care?

I mean of they want to stay at a fraction of the market value and profit of their direct competitor, good for them.

I want a competitive market so I can have cheaper gpus.

It's Nvidia, AMD, and maybe Intel.

AMD is offering AMD Developer Cloud (https://www.amd.com/en/blogs/2025/introducing-the-amd-develo...)

"25 complimentary GPU hours (approximately $50 US of credit for a single MI300X GPU instance), available for 10 days. If you need additional hours, we've made it easy to request additional credits."

If they care about their future they should. I am a die hard AMD supporter and even I am getting over their mediocrity and what seems to be constant self sabotage in the GPU department.

It’s the AMD management . They just are recycling 20 year VP lifers at AMD to take over key projects

They could have slapped 48gb of vram on their new Radeon cards and they would have instantly sold out but that would cut into cousins profit margin at nvidia so that’s obviously a no go.

I have had trained on both large AMD and Nvidia clusters and your right AMD support is good. I never had to talk to Nvidia support. That was better.

They should care about the availability of their hardware so large customers don't have to find and fix their bugs. Let consumers do that...

> AMD doesn't care about you being able to do computing on their consumer GPUs

Makes it a little hard to develop for without consumer GPU support...

Aren't they addressing it with the unified UDNA architecture? That's going to be a thing in the future GPUs, making consumer and datacenter ones share the same arch.

Different architectures was probably a big reason for the above issue.

Except they forget people get to adopt technologies by learning them on their consumer hardware.

this is ROCm?

Yes, the mi300x/mi250 are best supported as they directly compete with data center gpus from Nvidia which actually make money. Desktop is a rounding error by comparison.

It’s the same software stack.

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