iPhone 14
Geekbench ML Score
1814
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 26 2024 06:21 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.3.1 |
| 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 |
| 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 | 5.56 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
924
173.0 IPS |
|
|
Image Classification (F16)
|
100% |
897
167.9 IPS |
|
|
Image Classification (I8)
|
99% |
871
163.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
584
9.76 IPS |
|
|
Image Segmentation (F16)
|
100% |
511
8.54 IPS |
|
|
Image Segmentation (I8)
|
100% |
502
8.39 IPS |
|
|
Pose Estimation (F32)
|
100% |
5009
6.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
9298
11.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
9012
10.9 IPS |
|
|
Object Detection (F32)
|
100% |
962
71.8 IPS |
|
|
Object Detection (F16)
|
100% |
981
73.2 IPS |
|
|
Object Detection (I8)
|
97% |
971
72.5 IPS |
|
|
Face Detection (F32)
|
100% |
1645
19.6 IPS |
|
|
Face Detection (F16)
|
100% |
1445
17.2 IPS |
|
|
Face Detection (I8)
|
99% |
1439
17.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
3005
23.3 IPS |
|
|
Depth Estimation (F16)
|
99% |
3404
26.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
3372
26.2 IPS |
|
|
Style Transfer (F32)
|
100% |
9240
12.2 IPS |
|
|
Style Transfer (F16)
|
100% |
10577
13.9 IPS |
|
|
Style Transfer (I8)
|
100% |
10889
14.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2256
80.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2488
88.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2477
88.5 IPS |
|
|
Text Classification (F32)
|
100% |
981
1.41 KIPS |
|
|
Text Classification (F16)
|
100% |
477
686.0 IPS |
|
|
Text Classification (I8)
|
96% |
639
919.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1288
23.7 IPS |
|
|
Machine Translation (F16)
|
99% |
1645
30.3 IPS |
|
|
Machine Translation (I8)
|
99% |
1261
23.2 IPS |
