iPhone 15 Pro
Geekbench AI Score
3626
Single Precision Score
5404
Half Precision Score
4481
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | sichunlam |
| Upload Date | August 15 2024 08:37 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1653
307.5 IPS |
|
|
Image Classification (HP)
|
100% |
2225
413.8 IPS |
|
|
Image Classification (Q)
|
99% |
2226
415.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1452
23.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1369
22.2 IPS |
|
|
Image Segmentation (Q)
|
100% |
1366
22.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7342
8.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
14988
17.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
13311
15.6 IPS |
|
|
Object Detection (SP)
|
100% |
1704
135.2 IPS |
|
|
Object Detection (HP)
|
97% |
2479
197.4 IPS |
|
|
Object Detection (Q)
|
94% |
1791
142.7 IPS |
|
|
Face Detection (SP)
|
100% |
2852
33.9 IPS |
|
|
Face Detection (HP)
|
100% |
4903
58.3 IPS |
|
|
Face Detection (Q)
|
100% |
3087
36.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5900
45.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
9227
71.3 IPS |
|
|
Depth Estimation (Q)
|
96% |
4777
37.0 IPS |
|
|
Style Transfer (SP)
|
100% |
19534
25.1 IPS |
|
|
Style Transfer (HP)
|
100% |
30069
38.7 IPS |
|
|
Style Transfer (Q)
|
100% |
30730
39.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4545
167.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5924
218.7 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
4149
153.7 IPS |
|
|
Text Classification (SP)
|
100% |
3123
4.17 KIPS |
|
|
Text Classification (HP)
|
100% |
5185
6.92 KIPS |
|
|
Text Classification (Q)
|
93% |
5258
7.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
2808
48.4 IPS |
|
|
Machine Translation (HP)
|
98% |
4497
77.7 IPS |
|
|
Machine Translation (Q)
|
98% |
4559
78.8 IPS |
