iPhone 14
Geekbench AI Score
3171
Single Precision Score
19750
Half Precision Score
22069
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | JC_Coronel |
| Upload Date | December 09 2024 06:34 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| Model | iPhone 14 |
| Model ID | iPhone14,7 |
| Motherboard | D27AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.58 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1366
254.0 IPS |
|
|
Image Classification (HP)
|
100% |
9003
1.67 KIPS |
|
|
Image Classification (Q)
|
96% |
8482
1.58 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1337
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
12322
199.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
14781
239.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5673
6.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
87916
102.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
90359
105.9 IPS |
|
|
Object Detection (SP)
|
100% |
1391
110.3 IPS |
|
|
Object Detection (HP)
|
99% |
10680
849.6 IPS |
|
|
Object Detection (Q)
|
91% |
11773
940.7 IPS |
|
|
Face Detection (SP)
|
100% |
2715
32.3 IPS |
|
|
Face Detection (HP)
|
100% |
26761
318.0 IPS |
|
|
Face Detection (Q)
|
100% |
33857
402.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
5219
40.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
54489
419.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
76846
600.5 IPS |
|
|
Style Transfer (SP)
|
100% |
16406
21.1 IPS |
|
|
Style Transfer (HP)
|
100% |
163099
209.7 IPS |
|
|
Style Transfer (Q)
|
96% |
166108
214.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3688
136.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28022
1.03 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
33251
1.23 KIPS |
|
|
Text Classification (SP)
|
100% |
2441
3.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2561
3.42 KIPS |
|
|
Text Classification (Q)
|
93% |
2505
3.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
3416
58.8 IPS |
|
|
Machine Translation (HP)
|
100% |
5081
87.5 IPS |
|
|
Machine Translation (Q)
|
98% |
5710
98.7 IPS |
