iPhone 14
Geekbench ML Score
1802
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 19 2024 05:32 PM |
| Views | 1 |
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% |
891
166.7 IPS |
|
|
Image Classification (F16)
|
100% |
838
156.7 IPS |
|
|
Image Classification (I8)
|
99% |
835
156.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
566
9.45 IPS |
|
|
Image Segmentation (F16)
|
100% |
491
8.20 IPS |
|
|
Image Segmentation (I8)
|
100% |
495
8.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
4888
5.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
9237
11.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
8932
10.8 IPS |
|
|
Object Detection (F32)
|
100% |
958
71.5 IPS |
|
|
Object Detection (F16)
|
100% |
984
73.4 IPS |
|
|
Object Detection (I8)
|
97% |
956
71.3 IPS |
|
|
Face Detection (F32)
|
100% |
1640
19.5 IPS |
|
|
Face Detection (F16)
|
100% |
1435
17.1 IPS |
|
|
Face Detection (I8)
|
99% |
1446
17.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
3009
23.3 IPS |
|
|
Depth Estimation (F16)
|
99% |
3499
27.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
3352
26.0 IPS |
|
|
Style Transfer (F32)
|
100% |
9241
12.2 IPS |
|
|
Style Transfer (F16)
|
100% |
10988
14.5 IPS |
|
|
Style Transfer (I8)
|
100% |
10930
14.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2288
81.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2517
89.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2496
89.1 IPS |
|
|
Text Classification (F32)
|
100% |
981
1.41 KIPS |
|
|
Text Classification (F16)
|
100% |
459
659.8 IPS |
|
|
Text Classification (I8)
|
96% |
644
925.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1302
24.0 IPS |
|
|
Machine Translation (F16)
|
99% |
1662
30.6 IPS |
|
|
Machine Translation (I8)
|
99% |
1276
23.5 IPS |
