iPhone 15
Geekbench AI Score
3472
Single Precision Score
23059
Half Precision Score
26094
Quantized Score
Geekbench AI 1.2.0 Corporate for iOS AArch64
Result Information
| Upload Date | December 01 2024 10:10 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| Model | iPhone 15 |
| Model ID | iPhone15,4 |
| Motherboard | D37AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.56 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1450
269.6 IPS |
|
|
Image Classification (HP)
|
100% |
10668
1.98 KIPS |
|
|
Image Classification (Q)
|
97% |
12910
2.41 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1472
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
14723
238.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
18096
293.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
6328
7.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
98487
114.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
103016
120.7 IPS |
|
|
Object Detection (SP)
|
100% |
1554
123.3 IPS |
|
|
Object Detection (HP)
|
100% |
12841
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14778
1.18 KIPS |
|
|
Face Detection (SP)
|
100% |
3281
39.0 IPS |
|
|
Face Detection (HP)
|
100% |
31610
375.6 IPS |
|
|
Face Detection (Q)
|
100% |
40285
478.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6032
46.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
76128
586.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
97191
759.9 IPS |
|
|
Style Transfer (SP)
|
100% |
17421
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
173108
222.5 IPS |
|
|
Style Transfer (Q)
|
96% |
176403
227.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3970
146.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32430
1.20 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
39921
1.47 KIPS |
|
|
Text Classification (SP)
|
100% |
2632
3.51 KIPS |
|
|
Text Classification (HP)
|
100% |
2770
3.70 KIPS |
|
|
Text Classification (Q)
|
93% |
2434
3.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
3373
58.1 IPS |
|
|
Machine Translation (HP)
|
100% |
5719
98.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6134
106.0 IPS |
