Mac Pro (2023)
Geekbench AI Score
4594
Single Precision Score
7228
Half Precision Score
5643
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | richh- |
| Upload Date | March 20 2025 06:44 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Ultra |
| System Information | |
|---|---|
| Operating System | macOS 15.3.2 (Build 24D81) |
| 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 | 3.68 GHz |
| Cluster 1 | 16 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 192.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1469
273.2 IPS |
|
|
Image Classification (HP)
|
100% |
2254
419.2 IPS |
|
|
Image Classification (Q)
|
96% |
1665
310.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1727
28.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2516
40.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3134
50.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
18169
21.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
32601
38.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
23386
27.4 IPS |
|
|
Object Detection (SP)
|
100% |
1870
148.3 IPS |
|
|
Object Detection (HP)
|
97% |
2877
229.0 IPS |
|
|
Object Detection (Q)
|
94% |
2041
162.7 IPS |
|
|
Face Detection (SP)
|
100% |
3747
44.5 IPS |
|
|
Face Detection (HP)
|
100% |
6127
72.8 IPS |
|
|
Face Detection (Q)
|
100% |
3635
43.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6592
50.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
12350
95.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
8229
64.3 IPS |
|
|
Style Transfer (SP)
|
100% |
28467
36.6 IPS |
|
|
Style Transfer (HP)
|
100% |
42880
55.1 IPS |
|
|
Style Transfer (Q)
|
96% |
32536
42.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6028
222.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8182
302.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5027
185.6 IPS |
|
|
Text Classification (SP)
|
100% |
2312
3.09 KIPS |
|
|
Text Classification (HP)
|
100% |
4032
5.38 KIPS |
|
|
Text Classification (Q)
|
93% |
4003
5.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
4961
85.5 IPS |
|
|
Machine Translation (HP)
|
98% |
6843
118.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6724
116.2 IPS |
