iPhone 15
Geekbench AI Score
3522
Single Precision Score
22809
Half Precision Score
25101
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | December 07 2024 02:54 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| 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% |
1414
263.0 IPS |
|
|
Image Classification (HP)
|
100% |
10113
1.88 KIPS |
|
|
Image Classification (Q)
|
97% |
11744
2.19 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1467
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
14650
237.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
17943
290.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6643
7.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
97228
113.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
101854
119.4 IPS |
|
|
Object Detection (SP)
|
100% |
1597
126.7 IPS |
|
|
Object Detection (HP)
|
100% |
12860
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14871
1.19 KIPS |
|
|
Face Detection (SP)
|
100% |
3288
39.1 IPS |
|
|
Face Detection (HP)
|
100% |
30862
366.7 IPS |
|
|
Face Detection (Q)
|
100% |
39880
473.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6059
46.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
75921
584.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
95395
745.8 IPS |
|
|
Style Transfer (SP)
|
100% |
17866
23.0 IPS |
|
|
Style Transfer (HP)
|
100% |
173979
223.7 IPS |
|
|
Style Transfer (Q)
|
96% |
178367
230.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4044
149.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31406
1.16 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38295
1.41 KIPS |
|
|
Text Classification (SP)
|
100% |
2665
3.56 KIPS |
|
|
Text Classification (HP)
|
100% |
2171
2.90 KIPS |
|
|
Text Classification (Q)
|
93% |
1461
1.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
3489
60.1 IPS |
|
|
Machine Translation (HP)
|
100% |
7405
127.5 IPS |
|
|
Machine Translation (Q)
|
98% |
8197
141.7 IPS |
