Mac Studio (2023)
Geekbench AI Score
4534
Single Precision Score
7019
Half Precision Score
5588
Quantized Score
Geekbench AI 1.4.0 for macOS AArch64
Result Information
| User | rmealey19 |
| Upload Date | July 09 2025 12:12 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Ultra |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| Model | Mac Studio (2023) |
| Model ID | Mac14,14 |
| Motherboard | Mac14,14 |
| CPU Information | |
|---|---|
| Name | Apple M2 Ultra |
| Topology | 1 Processor, 24 Cores |
| Identifier | Apple M2 Ultra |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 16 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1463
272.1 IPS |
|
|
Image Classification (HP)
|
100% |
2280
424.0 IPS |
|
|
Image Classification (Q)
|
96% |
1672
312.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1745
28.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2435
39.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
2975
48.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
18671
21.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
32238
37.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
23238
27.2 IPS |
|
|
Object Detection (SP)
|
100% |
1817
144.1 IPS |
|
|
Object Detection (HP)
|
97% |
2778
221.1 IPS |
|
|
Object Detection (Q)
|
94% |
2005
159.8 IPS |
|
|
Face Detection (SP)
|
100% |
3649
43.4 IPS |
|
|
Face Detection (HP)
|
100% |
5977
71.0 IPS |
|
|
Face Detection (Q)
|
100% |
3477
41.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6190
47.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
10572
81.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
7666
59.9 IPS |
|
|
Style Transfer (SP)
|
100% |
29588
38.0 IPS |
|
|
Style Transfer (HP)
|
100% |
41981
54.0 IPS |
|
|
Style Transfer (Q)
|
96% |
33213
42.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6008
221.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7536
278.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5028
185.6 IPS |
|
|
Text Classification (SP)
|
100% |
2390
3.19 KIPS |
|
|
Text Classification (HP)
|
100% |
4148
5.54 KIPS |
|
|
Text Classification (Q)
|
93% |
4148
5.57 KIPS |
|
|
Machine Translation (SP)
|
100% |
4425
76.2 IPS |
|
|
Machine Translation (HP)
|
98% |
7047
121.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6946
120.0 IPS |
