iPhone 14
Geekbench AI Score
1932
Single Precision Score
2027
Half Precision Score
1130
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | TheDogDR |
| Upload Date | October 10 2024 10:40 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.3.1 |
| 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 | 5.55 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
938
174.5 IPS |
|
|
Image Classification (HP)
|
100% |
938
174.5 IPS |
|
|
Image Classification (Q)
|
97% |
396
73.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
639
10.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
567
9.19 IPS |
|
|
Image Segmentation (Q)
|
99% |
485
7.86 IPS |
|
|
Pose Estimation (SP)
|
100% |
5517
6.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
10504
12.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
5325
6.24 IPS |
|
|
Object Detection (SP)
|
100% |
978
77.6 IPS |
|
|
Object Detection (HP)
|
98% |
1036
82.5 IPS |
|
|
Object Detection (Q)
|
94% |
458
36.5 IPS |
|
|
Face Detection (SP)
|
100% |
1705
20.3 IPS |
|
|
Face Detection (HP)
|
100% |
1601
19.0 IPS |
|
|
Face Detection (Q)
|
100% |
572
6.80 IPS |
|
|
Depth Estimation (SP)
|
100% |
3288
25.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
3598
27.8 IPS |
|
|
Depth Estimation (Q)
|
86% |
1631
12.7 IPS |
|
|
Style Transfer (SP)
|
100% |
9778
12.6 IPS |
|
|
Style Transfer (HP)
|
100% |
12132
15.6 IPS |
|
|
Style Transfer (Q)
|
96% |
6892
8.89 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2901
107.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2526
93.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1002
37.0 IPS |
|
|
Text Classification (SP)
|
100% |
1028
1.37 KIPS |
|
|
Text Classification (HP)
|
100% |
627
836.7 IPS |
|
|
Text Classification (Q)
|
93% |
624
837.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1374
23.7 IPS |
|
|
Machine Translation (HP)
|
96% |
1834
31.7 IPS |
|
|
Machine Translation (Q)
|
98% |
1808
31.3 IPS |
