I don't understand this stance. Microsoft is reliant on Nvidia, they don't have a good ARM SOC to ship with without them. They will bend over backwards to accommodate these SOCs on Windows, and probably don't have much work to do in the first place.

Apple's vertical integration has led to a Siri overhaul that took half a decade to roll out, and it won't even run locally. They built an NPU coprocessor that's basically dark silicon for expensive inference, and then shipped MLX to stop Tensorflow and Pytorch from replacing Apple's role in the stack entirely. Mac owners are pleading for signed CUDA drivers for the PCIe or Thunderbolt in their $5,000+ Mac Pros. Apple's ecosystem is pure liability for AI, they're not moving any product for datacenter inference and can't even sell the hardware to themselves: https://9to5mac.com/2026/03/02/some-apple-ai-servers-are-rep...

Nvidia's profit margins are safe. Even if the RTX Spark is a completely failed product, Apple is not encroaching on the markets that Nvidia dominates.

▲

Xeoncross 31 minutes ago | parent | next [-]

While I do not use Apple's own intelligence models/apps, I happily run Qwen 3.6 / Gemma 4 on my $1k macbook instead of paying for Sonnet.

It's still early and requires more fiddling than should be needed for regular people, but I'm good right now and can run my models locally on the laptop I use for everything already.

All that has to happen now is models improving (keeps happening) and oMLX, LM Studio, llamma, Ollama, etc.. to get simpler with more hand-holding and sane defaults.

▲

h14h an hour ago | parent | prev [-]

Fair points all around. Ultimately it all comes down to execution.

In theory, Apple SHOULD have an advantage given they have everything they need in house and can all pull in a unified direction. In practice, it's not always the case that all the teams in a large corporation are all that much better at pulling in the same direction than multiple different corporations in a partnership. And all this will be moot if Local LLMs never catch up to cloud LLMs in terms of quality.

Regardless, it'll be very interesting to see how Nvidia's partnerships with Microsoft & hardware OEMs play out. If the AI inference compute share shifts appreciably to local consumer hardware, I'll want to see strong competition.

	▲	bigyabai an hour ago \| parent [-]
		I'd argue that Apple had the upper hand, but they folded super early. They abandoned OpenCL, which was the most promising CUDA competitor with industry-wide buy in from dozens of companies. Then they transitioned to an ecosystem-first mindset prevented Apple from cooperating to take down Nvidia, and their locked-down software stopped the industry's first high-speed ARM servers from reaching their audience. Nvidia capitalized on both opportunities to the tune of trillions in valuation. Without Khronos involved, I don't think that Apple has the buy-in to create a real industry-scale CUDA alternative. At this point, it might just be most profitable to support CUDA in macOS and give the people what they want.