iPhone 14 Pro
Geekbench AI Score
3565
Single Precision Score
23291
Half Precision Score
26955
Quantized Score
Geekbench AI 1.4.0-Beta1 Corporate for iOS AArch64
Result Information
| Upload Date | June 06 2025 07:46 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| Model | iPhone 14 Pro |
| Model ID | iPhone15,2 |
| Motherboard | D73AP |
| 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 | 5.53 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1437
267.3 IPS |
|
|
Image Classification (HP)
|
100% |
10023
1.86 KIPS |
|
|
Image Classification (Q)
|
97% |
11860
2.21 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1426
23.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15891
257.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
19503
316.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7021
8.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
103800
121.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
105446
123.6 IPS |
|
|
Object Detection (SP)
|
100% |
1578
125.2 IPS |
|
|
Object Detection (HP)
|
100% |
13019
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
14952
1.19 KIPS |
|
|
Face Detection (SP)
|
100% |
3093
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
31730
377.0 IPS |
|
|
Face Detection (Q)
|
100% |
40181
477.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6135
47.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
75395
580.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
95574
747.2 IPS |
|
|
Style Transfer (SP)
|
100% |
19097
24.5 IPS |
|
|
Style Transfer (HP)
|
100% |
171274
220.2 IPS |
|
|
Style Transfer (Q)
|
96% |
171414
221.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4235
156.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33414
1.23 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37580
1.39 KIPS |
|
|
Text Classification (SP)
|
100% |
2717
3.63 KIPS |
|
|
Text Classification (HP)
|
100% |
2122
2.83 KIPS |
|
|
Text Classification (Q)
|
93% |
2621
3.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
3507
60.4 IPS |
|
|
Machine Translation (HP)
|
100% |
7513
129.4 IPS |
|
|
Machine Translation (Q)
|
98% |
8565
148.0 IPS |
