Apple SiliconApple

Apple M2 Ultra (76c GPU, 192GB)

Name: Apple M2 Ultra (76c GPU, 192GB)
Brand: Apple
SKU: apple-m2-ultra

Curated Aggregate·2024-04-093 workloads · 3 records

MyAI RatingNot scoredInsufficient comparison evidence

VRAM

192 GB

TDP

80 W

MSRP

$7.0k

Perf/W

0.75 tok/s/W

Cost/1K tok

$0.0012/k

Tested

2024-04-09

Quick answer

How fast is Apple M2 Ultra (76c GPU, 192GB) for local AI workloads?

Apple M2 Ultra (76c GPU, 192GB) has a source-attributed result of 32.0 tok/s on Qwen 2.5 14B (batch 1, 8192-token context, Q4_K_M; runtime not documented). This is a reference report, not an independently verified lab result. A 70B Q4_K_M artifact needs roughly 40GB for weights alone; smaller memory configurations require explicit offload or model splitting and do not establish full-GPU residency.

Verdict

Apple M2 Ultra (76c GPU, 192GB) with 192GB VRAM at 80W TDP, scored across 3 workloads with 3 benchmark records.

Reference workload

Qwen 2.5 14B

32 tok/s

Quantization

Q4_K_M

8K context · batch 1

LLM Inference Performance

Benchmarks (3 workloads)

Workload	Score	Quant	Context	σ	Status	Tested
Mistral 7B llm	60.0tok/s	Q4_K_M	4K	,	Curated Aggregate	2024-04-09
Gemma 2 9B llm	44.0tok/s	Q4_K_M	8K	,	Curated Aggregate	2024-07-12
Qwen 2.5 14B llm	32.0tok/s	Q4_K_M	8K	,	Curated Aggregate	2024-10-04

MyAI Score: not scored

There is insufficient comparable evidence to score Apple M2 Ultra (76c GPU, 192GB). A score needs results for multiple devices with matching workload, runtime version, quantization, context and batch size.

Workload Fit

Planning estimates for 192GB: weights plus at least 2GB or 10% overhead. Actual KV cache depends on model, context and cache format; confirm the artifact before buying.

FP16

7-8B

Excellent

13-14B

Excellent

32B

Excellent

70B

Excellent

Good

Reported batch-one examples

Qwen 2.5 14B32 tok/s

Gemma 2 9B44 tok/s

Mistral 7B60 tok/s

Source

Qwen 2.5 14B 4-bit MLX.

View source How we benchmark →

Public Trust Layer

Trust score

6/10

MyAI rating

Not scored

Runs

Not documented

Freshness

Stale

Source-linked row with explicit verification status.

Record date: 2024-10-04; 705 days old.

Open primary source

Best place to start

Where to buy

Search first

Retailer we'd check first

Amazon search

Amazon is a fast way to check live availability, but memory tier and exact SKU matter more than the first visible price.

Search Amazon listings

+Cross-check the current ask against $7.0k and any reputable open-box or used options.
+Verify RAM, storage, and chip binning carefully. Small spec differences change AI usability dramatically.
+If you plan long 24/7 inference runs, warranty and thermals matter more than a tiny discount.

There is insufficient comparable evidence for a purchase recommendation. Check model fit, software support and a current seller quote.

Affiliate note: we do not have a device-level ASIN yet, so this opens tagged Amazon search results for the exact product name.