Mac vs NVIDIA vs AMD for Local AI
We default to Mac for local AI. A Mac holds more model memory per box than any other machine we can buy, it is quiet and small, and it needs little maintenance. It is not the fastest machine for every model, and it is not the right answer for every business. This post explains both halves, with figures as of October 2026.
Why memory decides
A model has to fit in memory to run at all. On a PC with a discrete graphics card, it has to fit in the card's own memory: 32 GB on an NVIDIA RTX 5090, 96 GB on an RTX PRO 6000 Blackwell.
Apple silicon uses unified memory. The CPU and GPU share one pool, and the whole pool is available to the model. As of October 2026, a Mac Studio M5 Ultra holds up to 256 GB. A 512 GB configuration ships in late October 2026; Apple has not published its price.
Apple is no longer the only maker of unified-memory machines. NVIDIA's DGX Spark and AMD's Strix Halo systems (the Ryzen AI Max+ 395) both reach 128 GB. NVIDIA's RTX Spark, a Windows-on-Arm design from the same chip family, also reaches 128 GB, with systems from ASUS, Acer and MSI expected in October 2026 and no pricing announced. The Mac's lead is capacity: twice the memory of the largest of these as of October 2026, and four times when the 512 GB model ships.
What each platform offers, as of October 2026
| Platform | Memory | Bandwidth | Price | Software |
|---|---|---|---|---|
| Mac Studio M5 Ultra | 96 or 256 GB (512 GB late October) | 1.2 TB/s | from $5,499; $9,499 with 256 GB | macOS, MLX |
| NVIDIA DGX Spark | 128 GB (64 GB version from October 23) | 273 GB/s | about $6,950 for 128 GB (reported); $4,999 for 64 GB (reported) | Linux, CUDA |
| AMD Strix Halo mini PC | up to 128 GB | about 256 GB/s | about $3,000 to $3,450 for 128 GB (reported street range) | Windows or Linux, ROCm or Vulkan |
| NVIDIA RTX 5090 (card only) | 32 GB | 1,792 GB/s | about $4,300 to $4,800 street (reported) | CUDA |
| NVIDIA RTX PRO 6000 Blackwell (card only) | 96 GB | 1,792 GB/s | $16,000 list (reported) | CUDA |
Mac prices are Apple US retail. Prices on non-Apple hardware have moved monthly through the 2026 memory shortage. The DGX Spark launched at $3,999 in October 2025, rose to $4,699 in February 2026, and was reported near $6,950 in early October. The RTX 5090 launched at a $1,999 list price. The graphics-card rows exclude the PC the card goes in.
Cost per gigabyte of model memory
Dividing price by memory gives a rough cost per gigabyte. These are estimates, as of October 2026:
| Platform | Approximate cost per GB |
|---|---|
| Strix Halo mini PC, 128 GB | about $25 |
| Mac Studio M5 Ultra, 256 GB | about $37 |
| DGX Spark, 128 GB | about $54 |
| RTX 5090, 32 GB (card only) | about $134 |
| RTX PRO 6000, 96 GB (card only) | about $167 |
Speed: where the Mac is faster and where it is not
Maai® Machines has not run its own benchmarks. These figures come from published reviews.
MacStories measured Qwen3.8 27B at 4-bit on a Mac Studio M5 Ultra in September 2026. Generation speed, in tokens per second:
| Context length | M5 Ultra | M3 Ultra | RTX 5090 PC |
|---|---|---|---|
| 8K | 48 | 31 | 59 |
| 64K | 39 | 23.5 | 51 |
| 128K | 32 | 20 | 44 |
The same review measured prompt processing on a 6,091-token prompt at 3,031 tokens per second on the RTX 5090 PC, 1,701 on the M5 Ultra and 414 on the M3 Ultra.
Hardware Corner (March 11, 2026) found the same pattern at a larger size. On Qwen3.5-122B-A10B, an M5 Max with 128 GB, in a MacBook Pro, generated 65.9 tokens per second, and an RTX PRO 6000 generated 50 to 65 percent faster.
Discrete NVIDIA cards have about six times the memory bandwidth of a Mac mini M5 Pro (1,792 GB/s against 307 GB/s). On models that fit in 32 to 96 GB, they are faster. The Mac is the machine that holds models too large for a single card.
Why we default to Mac
- Memory per box. Up to 256 GB as of October 2026, 512 GB from late October.
- Bandwidth for the capacity. 1.2 TB/s on the M5 Ultra.
- Quiet, small and low-maintenance. It sits in an office, not a server room.
- The software caught up. Ollama, the runtime we install, moved to Apple's MLX engine on Apple silicon in 2026, with its largest gains on M5 and M6 chips.
Clustering works too. Apple markets the Mac mini M5 Pro for clustering over Thunderbolt 5 to run models larger than one machine holds. The Mac mini M6 has Thunderbolt 4 and is not a cluster node.
When another platform is the better fit
We install and support Mac. We advise honestly on other platforms, and we quote non-Mac installs case by case. Another platform is usually the better fit when:
- The work needs CUDA. Fine-tuning, some image and video pipelines, and NVIDIA-only tools point to a DGX Spark or an RTX workstation.
- Speed matters most on models that fit in 32 to 96 GB. A discrete NVIDIA card is faster there.
- The lowest cost per gigabyte at 128 GB matters more than speed. Strix Halo systems cost least per gigabyte, as estimated above.
- The business requires Windows. Strix Halo or RTX Spark systems run it.
The setup matters
Hardware is half of a working system. The other half is choosing the model and quantization for your memory and work, sizing the context window, and configuring the stack: Ollama for inference, an agent framework for your workflows, Open WebUI for the interface, and Tailscale for secure remote access. We configure and test all of it on your machine before handoff.
The sizing guide covers which Mac fits which work, and the model guide covers which model to run. To talk it through, book a free 15-minute call.