iPhone 15
Geekbench AI Score
3423
Single Precision Score
19827
Half Precision Score
22539
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | Zuluman |
| Upload Date | September 18 2024 07:00 PM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
10281
1.91 KIPS |
|
|
Image Classification (Q)
|
97% |
12581
2.35 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1472
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
11743
190.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
13786
223.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6321
7.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
94734
110.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
102502
120.1 IPS |
|
|
Object Detection (SP)
|
100% |
1525
121.0 IPS |
|
|
Object Detection (HP)
|
100% |
12915
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14690
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
3231
38.4 IPS |
|
|
Face Detection (HP)
|
100% |
31347
372.5 IPS |
|
|
Face Detection (Q)
|
100% |
39714
471.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5928
45.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
74517
574.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
94501
738.9 IPS |
|
|
Style Transfer (SP)
|
100% |
16268
20.9 IPS |
|
|
Style Transfer (HP)
|
100% |
172399
221.6 IPS |
|
|
Style Transfer (Q)
|
96% |
172893
223.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3917
144.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31803
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37948
1.40 KIPS |
|
|
Text Classification (SP)
|
100% |
2613
3.49 KIPS |
|
|
Text Classification (HP)
|
100% |
2271
3.03 KIPS |
|
|
Text Classification (Q)
|
93% |
2428
3.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
3370
58.0 IPS |
|
|
Machine Translation (HP)
|
100% |
2186
37.7 IPS |
|
|
Machine Translation (Q)
|
98% |
2167
37.5 IPS |
