Mac Pro (2023)
Geekbench AI Score
4570
Single Precision Score
7174
Half Precision Score
5625
Quantized Score
Geekbench AI 1.1.0 Pro for macOS AArch64
Result Information
| User | Gonfonix |
| Upload Date | November 10 2024 02:00 AM |
| Views | 6 |
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 | 3.67 GHz |
| Cluster 1 | 16 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 192.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1456
270.8 IPS |
|
|
Image Classification (HP)
|
100% |
2255
419.3 IPS |
|
|
Image Classification (Q)
|
96% |
1661
310.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1794
29.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2507
40.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3125
50.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
18611
21.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
31687
37.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
23549
27.6 IPS |
|
|
Object Detection (SP)
|
100% |
1855
147.1 IPS |
|
|
Object Detection (HP)
|
97% |
2919
232.4 IPS |
|
|
Object Detection (Q)
|
94% |
2070
165.0 IPS |
|
|
Face Detection (SP)
|
100% |
3645
43.3 IPS |
|
|
Face Detection (HP)
|
100% |
6393
76.0 IPS |
|
|
Face Detection (Q)
|
100% |
3644
43.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6421
49.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12003
92.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
8167
63.8 IPS |
|
|
Style Transfer (SP)
|
100% |
27095
34.8 IPS |
|
|
Style Transfer (HP)
|
100% |
41688
53.6 IPS |
|
|
Style Transfer (Q)
|
96% |
32134
41.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5972
220.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8106
299.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4983
184.0 IPS |
|
|
Text Classification (SP)
|
100% |
2344
3.13 KIPS |
|
|
Text Classification (HP)
|
100% |
4067
5.43 KIPS |
|
|
Text Classification (Q)
|
93% |
4054
5.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
4964
85.5 IPS |
|
|
Machine Translation (HP)
|
98% |
6550
113.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6493
112.2 IPS |
