iPhone 15
Geekbench AI Score
1635
Single Precision Score
2732
Half Precision Score
2189
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | December 14 2024 03:06 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
606
112.6 IPS |
|
|
Image Classification (HP)
|
100% |
1084
201.5 IPS |
|
|
Image Classification (Q)
|
96% |
738
137.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
708
11.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1019
16.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
1165
18.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3022
3.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
6451
7.53 IPS |
|
|
Pose Estimation (Q)
|
95% |
5753
6.74 IPS |
|
|
Object Detection (SP)
|
100% |
706
56.0 IPS |
|
|
Object Detection (HP)
|
97% |
1323
105.4 IPS |
|
|
Object Detection (Q)
|
94% |
912
72.7 IPS |
|
|
Face Detection (SP)
|
100% |
1715
20.4 IPS |
|
|
Face Detection (HP)
|
100% |
2783
33.1 IPS |
|
|
Face Detection (Q)
|
100% |
1524
18.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2723
21.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
5489
42.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
3639
28.4 IPS |
|
|
Style Transfer (SP)
|
100% |
8287
10.7 IPS |
|
|
Style Transfer (HP)
|
100% |
12372
15.9 IPS |
|
|
Style Transfer (Q)
|
96% |
10453
13.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1902
70.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2219
81.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1646
60.8 IPS |
|
|
Text Classification (SP)
|
100% |
1227
1.64 KIPS |
|
|
Text Classification (HP)
|
100% |
2117
2.83 KIPS |
|
|
Text Classification (Q)
|
93% |
2138
2.87 KIPS |
|
|
Machine Translation (SP)
|
100% |
1652
28.4 IPS |
|
|
Machine Translation (HP)
|
98% |
2774
47.9 IPS |
|
|
Machine Translation (Q)
|
98% |
2756
47.6 IPS |
