aliteq.

Apple M2 Ultra: 192 GB, what it runs and what it costs

Specs checked · Aliteq Team · How we compute this

The short answer

The Apple M2 Ultra has 192 GB of VRAM and 819.2 GB/s of memory bandwidth (2023). At Q4_K_M quality or better with an 8K context it runs 43 of the open models we track; the largest that fits with room to spare is Qwen3.5 122B-A10B (MoE). We don't see it for rent on the providers we track right now.

VRAM
192 GB
Bandwidth
819.2 GB/s
Board power
—
Launched
2023

Source: Apple specification · bandwidth not yet confirmed by a second source, so we don't estimate speed from it

Buy it or rent it

Not for rent on the providers we track right now. See every card that is.

Which AI models run on the Apple M2 Ultra

Computed by our VRAM engine for an 8K context: the best quality each model fits at in 192 GB. Speeds are upper-bound estimates from memory bandwidth, not benchmarks.

ModelBest fitVRAM used~tok/s
Qwen3 235B-A22B (MoE)Q6_K182 GB95% · tight—
MiniMax-M2.5 (MoE)Q6_K177 GB92% · tight—
Qwen3.8-Flash-Next (MoE)Q8_0179 GB93% · tight—
Qwen3.5 122B-A10B (MoE)Q8_0125 GB65%—
NVIDIA Nemotron 3 Super 120B-A12B (MoE)Q8_0123 GB64%—
gpt-oss 120B (MoE)Q8_0117 GB61%—
Llama 4 Scout 17B-16E (MoE)Q8_0109 GB57%—
GLM-4.5-Air (MoE)Q8_0107 GB56%—
Qwen3-Next 80B-A3B (MoE)F16150 GB78%—
Qwen3-Coder-Next 80B-A3B (MoE)F16149 GB78%—
DeepSeek R1 Distill 70BF16135 GB70%—
Mixtral 8x7B (MoE)F1689 GB46%—

Fits only below Q4 quality: MiniMax-M3 (MoE) (Q2_K).

Too big for 192 GB (rent a bigger card instead): what it costs to run GLM-5.3 (MoE), what it costs to run DeepSeek V4.1 Flash (MoE), what it costs to run DeepSeek V4 Pro (MoE), what it costs to run Kimi K3 (MoE).

Check a model and context of your own in the VRAM calculator.

Cards to compare it with

Every card by VRAM tier: all GPUs for gaming and local AI.

Apple M2 Ultra: common questions

How much VRAM does the Apple M2 Ultra have?
192 GB, with 819.2 GB/s of memory bandwidth, per the maker's specification.
What is the biggest AI model the Apple M2 Ultra can run?
Of the open models we track, Qwen3.5 122B-A10B (MoE) is the largest that fits at Q4_K_M or better with an 8K context and room to spare (about 125 GB of 192 GB). Qwen3 235B-A22B (MoE) also squeezes in, but with almost no memory left for longer context. Bigger models only fit at lower-quality quants or need more memory.
Can I rent an Apple M2 Ultra in the cloud?
We don't see it on Vast.ai, Runpod or the other providers we track right now. The cloud GPU table lists every card that is for rent.
Is 192 GB enough?
Datacenter GPUs and unified-memory machines; mostly rented by the hour.