iPhone 15
Geekbench AI Score
3325
Single Precision Score
19882
Half Precision Score
22077
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | wangshuy |
| Upload Date | September 12 2024 07:52 AM |
| Views | 5 |
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% |
1411
262.3 IPS |
|
|
Image Classification (HP)
|
100% |
10517
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
12814
2.39 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1378
22.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
11739
190.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
13243
214.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
5644
6.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
91217
106.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
103581
121.4 IPS |
|
|
Object Detection (SP)
|
100% |
1474
116.9 IPS |
|
|
Object Detection (HP)
|
100% |
12893
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14585
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
3162
37.6 IPS |
|
|
Face Detection (HP)
|
100% |
31044
368.9 IPS |
|
|
Face Detection (Q)
|
100% |
38669
459.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5600
43.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
74117
571.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
94472
738.6 IPS |
|
|
Style Transfer (SP)
|
100% |
16853
21.7 IPS |
|
|
Style Transfer (HP)
|
100% |
171937
221.0 IPS |
|
|
Style Transfer (Q)
|
96% |
179372
231.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3831
141.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31635
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37776
1.39 KIPS |
|
|
Text Classification (SP)
|
100% |
2643
3.53 KIPS |
|
|
Text Classification (HP)
|
100% |
2452
3.27 KIPS |
|
|
Text Classification (Q)
|
93% |
2035
2.73 KIPS |
|
|
Machine Translation (SP)
|
100% |
3380
58.2 IPS |
|
|
Machine Translation (HP)
|
100% |
2167
37.3 IPS |
|
|
Machine Translation (Q)
|
98% |
2130
36.8 IPS |
