iPhone 14 Pro
Geekbench AI Score
2370
Single Precision Score
13003
Half Precision Score
13778
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | andrewkendall |
| Upload Date | August 15 2024 09:41 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 5.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1232
229.1 IPS |
|
|
Image Classification (HP)
|
100% |
5770
1.07 KIPS |
|
|
Image Classification (Q)
|
99% |
5904
1.10 KIPS |
|
|
Image Segmentation (SP)
|
100% |
752
12.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5074
82.3 IPS |
|
|
Image Segmentation (Q)
|
100% |
5131
83.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6414
7.48 IPS |
|
|
Pose Estimation (HP)
|
100% |
80283
93.7 IPS |
|
|
Pose Estimation (Q)
|
94% |
84824
99.5 IPS |
|
|
Object Detection (SP)
|
100% |
1301
103.2 IPS |
|
|
Object Detection (HP)
|
100% |
7863
623.7 IPS |
|
|
Object Detection (Q)
|
93% |
8442
673.6 IPS |
|
|
Face Detection (SP)
|
100% |
2166
25.7 IPS |
|
|
Face Detection (HP)
|
100% |
11090
131.8 IPS |
|
|
Face Detection (Q)
|
100% |
13026
154.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4051
31.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
43263
333.3 IPS |
|
|
Depth Estimation (Q)
|
97% |
46663
360.8 IPS |
|
|
Style Transfer (SP)
|
100% |
11062
14.2 IPS |
|
|
Style Transfer (HP)
|
100% |
122384
157.3 IPS |
|
|
Style Transfer (Q)
|
100% |
122322
157.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3245
119.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16704
616.8 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
21268
788.0 IPS |
|
|
Text Classification (SP)
|
100% |
1398
1.87 KIPS |
|
|
Text Classification (HP)
|
100% |
3347
4.47 KIPS |
|
|
Text Classification (Q)
|
93% |
3195
4.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
1647
28.4 IPS |
|
|
Machine Translation (HP)
|
100% |
2279
39.3 IPS |
|
|
Machine Translation (Q)
|
98% |
2251
38.9 IPS |
