iPhone 15
Geekbench AI Score
3365
Single Precision Score
19985
Half Precision Score
22959
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | guylafaras |
| Upload Date | September 30 2024 03:01 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1405
261.4 IPS |
|
|
Image Classification (HP)
|
100% |
10251
1.91 KIPS |
|
|
Image Classification (Q)
|
97% |
11963
2.23 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1453
23.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
14230
230.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
18250
295.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5716
6.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
92231
107.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
102233
119.8 IPS |
|
|
Object Detection (SP)
|
100% |
1514
120.1 IPS |
|
|
Object Detection (HP)
|
100% |
12850
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14881
1.19 KIPS |
|
|
Face Detection (SP)
|
100% |
3231
38.4 IPS |
|
|
Face Detection (HP)
|
100% |
31333
372.3 IPS |
|
|
Face Detection (Q)
|
100% |
39703
471.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5685
43.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
75964
585.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
96777
756.6 IPS |
|
|
Style Transfer (SP)
|
100% |
16756
21.5 IPS |
|
|
Style Transfer (HP)
|
100% |
171208
220.1 IPS |
|
|
Style Transfer (Q)
|
96% |
178484
230.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3806
140.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31975
1.18 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36399
1.34 KIPS |
|
|
Text Classification (SP)
|
100% |
2611
3.49 KIPS |
|
|
Text Classification (HP)
|
100% |
2079
2.77 KIPS |
|
|
Text Classification (Q)
|
93% |
2244
3.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
3450
59.4 IPS |
|
|
Machine Translation (HP)
|
100% |
2171
37.4 IPS |
|
|
Machine Translation (Q)
|
98% |
2188
37.8 IPS |
