iPhone 15 Pro
Geekbench AI Score
2633
Single Precision Score
13744
Half Precision Score
15523
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | yugene |
| Upload Date | August 17 2024 02:54 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| 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% |
1402
260.7 IPS |
|
|
Image Classification (HP)
|
100% |
6232
1.16 KIPS |
|
|
Image Classification (Q)
|
99% |
6877
1.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
806
13.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5220
84.6 IPS |
|
|
Image Segmentation (Q)
|
100% |
5209
84.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7321
8.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
87235
101.8 IPS |
|
|
Pose Estimation (Q)
|
94% |
131020
153.7 IPS |
|
|
Object Detection (SP)
|
100% |
1400
111.0 IPS |
|
|
Object Detection (HP)
|
100% |
8149
646.4 IPS |
|
|
Object Detection (Q)
|
93% |
8960
714.9 IPS |
|
|
Face Detection (SP)
|
100% |
2135
25.4 IPS |
|
|
Face Detection (HP)
|
100% |
10704
127.2 IPS |
|
|
Face Detection (Q)
|
100% |
12649
150.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4385
33.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
43123
332.2 IPS |
|
|
Depth Estimation (Q)
|
97% |
47415
366.6 IPS |
|
|
Style Transfer (SP)
|
100% |
11602
14.9 IPS |
|
|
Style Transfer (HP)
|
100% |
128079
164.6 IPS |
|
|
Style Transfer (Q)
|
100% |
128097
164.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3873
143.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18548
684.9 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
24086
892.4 IPS |
|
|
Text Classification (SP)
|
100% |
1772
2.36 KIPS |
|
|
Text Classification (HP)
|
71% |
4079
5.87 KIPS |
|
|
Text Classification (Q)
|
69% |
4541
6.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
1859
32.0 IPS |
|
|
Machine Translation (HP)
|
100% |
2326
40.1 IPS |
|
|
Machine Translation (Q)
|
98% |
2300
39.7 IPS |
