iPhone 15
Geekbench AI Score
1611
Single Precision Score
2713
Half Precision Score
2173
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | piotrowy |
| Upload Date | January 25 2025 09:42 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.2.1 |
| 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% |
607
112.9 IPS |
|
|
Image Classification (HP)
|
100% |
1056
196.5 IPS |
|
|
Image Classification (Q)
|
96% |
732
136.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
708
11.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1012
16.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
1167
18.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2992
3.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
6369
7.43 IPS |
|
|
Pose Estimation (Q)
|
95% |
5559
6.52 IPS |
|
|
Object Detection (SP)
|
100% |
668
52.9 IPS |
|
|
Object Detection (HP)
|
97% |
1274
101.5 IPS |
|
|
Object Detection (Q)
|
94% |
902
71.9 IPS |
|
|
Face Detection (SP)
|
100% |
1672
19.9 IPS |
|
|
Face Detection (HP)
|
100% |
2832
33.7 IPS |
|
|
Face Detection (Q)
|
100% |
1499
17.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2702
20.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
5368
41.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
3645
28.5 IPS |
|
|
Style Transfer (SP)
|
100% |
7958
10.2 IPS |
|
|
Style Transfer (HP)
|
100% |
12375
15.9 IPS |
|
|
Style Transfer (Q)
|
96% |
10356
13.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1916
70.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2221
82.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1662
61.4 IPS |
|
|
Text Classification (SP)
|
100% |
1238
1.65 KIPS |
|
|
Text Classification (HP)
|
100% |
2149
2.87 KIPS |
|
|
Text Classification (Q)
|
93% |
2106
2.83 KIPS |
|
|
Machine Translation (SP)
|
100% |
1615
27.8 IPS |
|
|
Machine Translation (HP)
|
98% |
2780
48.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2769
47.9 IPS |
