Mac Pro (2023)
Geekbench AI Score
4178
Single Precision Score
6592
Half Precision Score
5156
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | look234 |
| Upload Date | October 28 2024 11:32 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Ultra |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| Model | Mac Pro (2023) |
| Model ID | Mac14,8 |
| Motherboard | Mac14,8 |
| CPU Information | |
|---|---|
| Name | Apple M2 Ultra |
| Topology | 1 Processor, 24 Cores |
| Identifier | Apple M2 Ultra |
| Base Frequency | 3.65 GHz |
| Cluster 1 | 16 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1354
251.8 IPS |
|
|
Image Classification (HP)
|
100% |
1935
359.8 IPS |
|
|
Image Classification (Q)
|
96% |
1507
281.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1645
26.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2417
39.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
2917
47.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
18290
21.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
32004
37.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
23865
28.0 IPS |
|
|
Object Detection (SP)
|
100% |
1702
135.0 IPS |
|
|
Object Detection (HP)
|
97% |
2693
214.4 IPS |
|
|
Object Detection (Q)
|
94% |
1831
146.0 IPS |
|
|
Face Detection (SP)
|
100% |
3266
38.8 IPS |
|
|
Face Detection (HP)
|
100% |
5794
68.8 IPS |
|
|
Face Detection (Q)
|
100% |
3184
37.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5626
43.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
10298
79.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
7016
54.8 IPS |
|
|
Style Transfer (SP)
|
100% |
24411
31.4 IPS |
|
|
Style Transfer (HP)
|
100% |
42162
54.2 IPS |
|
|
Style Transfer (Q)
|
96% |
28800
37.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5107
188.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6839
252.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4448
164.3 IPS |
|
|
Text Classification (SP)
|
100% |
2161
2.88 KIPS |
|
|
Text Classification (HP)
|
100% |
3533
4.72 KIPS |
|
|
Text Classification (Q)
|
93% |
3894
5.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
4733
81.5 IPS |
|
|
Machine Translation (HP)
|
98% |
6333
109.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6213
107.4 IPS |
