iPhone 15
Geekbench AI Score
3418
Single Precision Score
22339
Half Precision Score
25870
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | Peritus |
| Upload Date | December 02 2024 08:31 AM |
| Views | 9 |
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% |
1452
270.0 IPS |
|
|
Image Classification (HP)
|
100% |
10201
1.90 KIPS |
|
|
Image Classification (Q)
|
97% |
13067
2.44 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1466
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
14254
231.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
18572
301.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6020
7.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
93653
109.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
102005
119.6 IPS |
|
|
Object Detection (SP)
|
100% |
1535
121.8 IPS |
|
|
Object Detection (HP)
|
100% |
12926
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
14742
1.18 KIPS |
|
|
Face Detection (SP)
|
100% |
3257
38.7 IPS |
|
|
Face Detection (HP)
|
100% |
32145
382.0 IPS |
|
|
Face Detection (Q)
|
100% |
41126
488.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5829
44.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
75555
582.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
96844
757.2 IPS |
|
|
Style Transfer (SP)
|
100% |
16896
21.7 IPS |
|
|
Style Transfer (HP)
|
100% |
168160
216.2 IPS |
|
|
Style Transfer (Q)
|
96% |
173816
224.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3904
144.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31613
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36609
1.35 KIPS |
|
|
Text Classification (SP)
|
100% |
2613
3.49 KIPS |
|
|
Text Classification (HP)
|
100% |
2405
3.21 KIPS |
|
|
Text Classification (Q)
|
93% |
2420
3.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
3390
58.4 IPS |
|
|
Machine Translation (HP)
|
100% |
5663
97.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6001
103.7 IPS |
