iPhone 14 Pro
Geekbench ML Score
3605
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | morglor |
| Upload Date | April 03 2024 02:41 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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 |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 5.50 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1442
269.9 IPS |
|
|
Image Classification (F16)
|
100% |
1853
346.7 IPS |
|
|
Image Classification (I8)
|
99% |
1866
349.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
802
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
812
13.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
804
13.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
6339
7.68 IPS |
|
|
Pose Estimation (F16)
|
100% |
14317
17.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
14268
17.3 IPS |
|
|
Object Detection (F32)
|
100% |
1446
108.0 IPS |
|
|
Object Detection (F16)
|
100% |
2008
149.9 IPS |
|
|
Object Detection (I8)
|
97% |
1448
108.1 IPS |
|
|
Face Detection (F32)
|
100% |
2780
33.1 IPS |
|
|
Face Detection (F16)
|
97% |
4442
52.8 IPS |
|
|
Face Detection (I8)
|
97% |
4432
52.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
5654
43.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8818
68.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
8790
68.2 IPS |
|
|
Style Transfer (F32)
|
100% |
17715
23.3 IPS |
|
|
Style Transfer (F16)
|
100% |
26918
35.4 IPS |
|
|
Style Transfer (I8)
|
100% |
26930
35.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4112
146.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5199
185.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5338
190.6 IPS |
|
|
Text Classification (F32)
|
100% |
2431
3.49 KIPS |
|
|
Text Classification (F16)
|
100% |
4125
5.93 KIPS |
|
|
Text Classification (I8)
|
96% |
3975
5.71 KIPS |
|
|
Machine Translation (F32)
|
100% |
1311
24.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1567
28.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1251
23.0 IPS |
