iPhone 15 Pro
Geekbench AI Score
3579
Single Precision Score
20527
Half Precision Score
25782
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | Bhealey |
| Upload Date | August 17 2024 01:31 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1556
289.3 IPS |
|
|
Image Classification (HP)
|
100% |
11963
2.22 KIPS |
|
|
Image Classification (Q)
|
99% |
13183
2.46 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1488
24.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
10491
170.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
10579
171.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6117
7.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
91702
107.0 IPS |
|
|
Pose Estimation (Q)
|
94% |
186635
218.9 IPS |
|
|
Object Detection (SP)
|
100% |
1567
124.3 IPS |
|
|
Object Detection (HP)
|
100% |
12534
994.2 IPS |
|
|
Object Detection (Q)
|
91% |
18275
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
3002
35.7 IPS |
|
|
Face Detection (HP)
|
100% |
21959
260.9 IPS |
|
|
Face Detection (Q)
|
100% |
35237
418.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6313
48.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
63468
489.0 IPS |
|
|
Depth Estimation (Q)
|
97% |
68896
532.7 IPS |
|
|
Style Transfer (SP)
|
100% |
18468
23.7 IPS |
|
|
Style Transfer (HP)
|
100% |
138594
178.2 IPS |
|
|
Style Transfer (Q)
|
100% |
139565
179.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4393
162.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32825
1.21 KIPS |
|
|
Image Super-Resolution (Q)
|
98% |
54129
2.01 KIPS |
|
|
Text Classification (SP)
|
100% |
3156
4.21 KIPS |
|
|
Text Classification (HP)
|
100% |
2437
3.25 KIPS |
|
|
Text Classification (Q)
|
93% |
2062
2.77 KIPS |
|
|
Machine Translation (SP)
|
100% |
3208
55.3 IPS |
|
|
Machine Translation (HP)
|
100% |
5960
102.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7215
124.7 IPS |
