The machine
Apple unveiled the new Mac Studio in late August with two chips: M5 Max and M5 Ultra. Most configurations started arriving September 22. The 512GB unified memory configuration of the M5 Ultra model is the exception. It ships in late October, and it is the one that matters for this story.
The numbers, from Apple's own announcement: a 36-core CPU, an 80-core GPU, 512GB of unified memory at 1.2TB/s of bandwidth, and a claimed 4.3x AI performance uplift over the M3 Ultra. Support for up to eight displays, including four Studio Display XDR monitors at full 5K and 120Hz. USB-C genlock support for syncing displays with professional camera capture, including iPhone 17 Pro setups. It runs macOS 27, Golden Gate, with Apple Intelligence and the new Liquid Glass interface refinements.
Pricing: the M5 Ultra Mac Studio starts at $5,499 in the US ($5,099 education). The 512GB configuration will land well above $10,000 once you stack the memory upgrade on top. Apple is also pushing its Apple Upgrade leasing program, $110.10 a month for 36 months on the M5 Ultra, which tells you who the target buyer is: professionals and enterprises expensing it, not hobbyists.
The curious case of the missing 512GB
The late-October date has a backstory worth knowing. The previous-generation Mac Studio offered a 512GB configuration, and Apple pulled it in March during the memory chip shortage. This is not a new tier. It is the return of a tier the market took away.
That matters because it tells you something about the memory market both vendors are living in. Apple could not reliably source the chips for a 512GB desktop six months ago. NVIDIA's RTX Spark partners are launching into that same market right now, with RAM reportedly eating up to 60 percent of the bill of materials on some laptops. When both Apple and NVIDIA are telling you memory is the constraint, believe them. The silicon is ready. The DRAM is the drama.
It also tells you who is buying. Apple has been unusually direct that the driver for the 512GB configuration is enterprise appetite for running larger AI models and autonomous agents locally. This is not a prosumer flex. It is companies that would rather buy a $12,000 desktop than pay cloud inference bills forever, or that cannot send their data to the cloud at all.
Why Windows readers should care
Fair question, and here is the honest answer. Nobody reading this is choosing between a Mac Studio and a Yoga 9n for the same desk. But everyone in the Windows ecosystem is about to hear "128GB unified memory" marketed as a breakthrough, and you deserve to know the context: Apple is shipping 512GB in the same quarter.
The comparison is the point, and it cuts both ways. On raw memory capacity, the Mac Studio exists in a different universe: 512GB versus 128GB, 1.2TB/s of bandwidth, a mature unified-memory architecture that Apple has been refining since the M1. If your workload is "load the biggest open model you can find and run it locally," the Mac Studio is the ceiling, and it is not close.
But the RTX Spark story was never about beating Apple at the $10,000 workstation game. It is about bringing a meaningful fraction of that capability to a $2,000 laptop. A 128GB RTX Spark machine that runs a 120-billion-parameter model is playing a different sport than a 512GB Mac Studio running something four times larger. The question is not which is faster. The question is whether the laptop-priced version is good enough for the work most people actually do.
There is also the software dimension. Apple's local-AI story runs through Apple Intelligence, MLX, and a developer ecosystem that has spent four years optimizing for unified memory. NVIDIA's runs through CUDA, Windows Agent Framework, llama.cpp, and vLLM. CUDA's ecosystem is vastly larger in the AI world, and native CUDA on a Windows laptop is something Apple cannot match at any price. The Mac Studio wins on memory capacity. The RTX Spark machines may win on the software developers actually use.
The real story: the local-AI workstation is now a category
Step back and look at what is happening. In the same month, Apple is shipping a 512GB AI workstation, NVIDIA is launching a 128GB AI PC platform with the entire Windows OEM bench, and Microsoft is holding an event to declare the local-AI PC era. Three years ago, "run the model locally" was a hobbyist thing you did with a gaming GPU and a lot of patience. Now it is the defining hardware narrative of the industry, with Apple, NVIDIA, and Microsoft all placing billion-dollar bets on it.
The economics driving this are straightforward. Cloud inference is a meter that never stops running. For enterprises with sustained AI workloads, or with data that cannot leave the building, a big local machine pays for itself. For everyone else, a laptop that runs a capable model privately, offline, with no subscription, is a genuinely new value proposition. The cloud is not going away. But the assumption that serious AI only happens in a data center is over.
What to watch from here: independent benchmarks comparing the M5 Ultra's AI performance against RTX Spark systems on real local workloads, not vendor slides. Memory pricing through the fourth quarter, which affects both platforms. And whether the enterprise buyers Apple is courting start showing up in NVIDIA's customer stories too, because that is when this stops being two separate launches and becomes one market.
The ceiling
If you want to know what "serious local AI" hardware looks like this fall, the 512GB M5 Ultra Mac Studio is the ceiling. Everything else gets measured against it, including the RTX Spark machines that start shipping this month. That is not an insult to NVIDIA. It is the compliment of being taken seriously. You only get compared to the best when people think you belong in the conversation.
Bottom line: Apple's 512GB Mac Studio is the benchmark for local-AI workstations and a reminder that memory, not silicon, is the industry's binding constraint. Windows readers should watch it the way runners watch the pacesetter: it shows where the race is going.