Mac Studio (2023)
Geekbench AI Score
4461
Single Precision Score
7218
Half Precision Score
5610
Quantized Score
Geekbench AI 1.4.0 for macOS AArch64
Result Information
| User | Rowles66 |
| Upload Date | July 09 2025 10:50 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Ultra |
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5306g) |
| 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 | 3.35 GHz |
| Cluster 1 | 16 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1421
264.2 IPS |
|
|
Image Classification (HP)
|
100% |
2241
416.7 IPS |
|
|
Image Classification (Q)
|
96% |
1598
298.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1662
26.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2384
38.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
2806
45.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
18144
21.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
36270
42.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
23949
28.1 IPS |
|
|
Object Detection (SP)
|
100% |
1735
137.6 IPS |
|
|
Object Detection (HP)
|
97% |
2649
210.9 IPS |
|
|
Object Detection (Q)
|
94% |
2004
159.7 IPS |
|
|
Face Detection (SP)
|
100% |
3596
42.7 IPS |
|
|
Face Detection (HP)
|
100% |
6163
73.2 IPS |
|
|
Face Detection (Q)
|
100% |
3418
40.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6181
47.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
11057
85.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
7611
59.5 IPS |
|
|
Style Transfer (SP)
|
100% |
31363
40.3 IPS |
|
|
Style Transfer (HP)
|
100% |
49748
64.0 IPS |
|
|
Style Transfer (Q)
|
96% |
37489
48.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5515
203.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7066
260.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4827
178.2 IPS |
|
|
Text Classification (SP)
|
100% |
2334
3.12 KIPS |
|
|
Text Classification (HP)
|
99% |
3965
5.29 KIPS |
|
|
Text Classification (Q)
|
93% |
3864
5.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
4682
80.6 IPS |
|
|
Machine Translation (HP)
|
98% |
7883
136.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7900
136.5 IPS |
