iPhone 14
Geekbench ML Score
873
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | benkis |
| Upload Date | May 09 2024 06:50 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.2 |
| 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% |
413
77.2 IPS |
|
|
Image Classification (F16)
|
100% |
385
72.1 IPS |
|
|
Image Classification (I8)
|
99% |
390
73.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
282
4.71 IPS |
|
|
Image Segmentation (F16)
|
100% |
249
4.15 IPS |
|
|
Image Segmentation (I8)
|
100% |
248
4.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
2551
3.09 IPS |
|
|
Pose Estimation (F16)
|
100% |
4054
4.91 IPS |
|
|
Pose Estimation (I8)
|
100% |
4068
4.93 IPS |
|
|
Object Detection (F32)
|
100% |
438
32.7 IPS |
|
|
Object Detection (F16)
|
100% |
446
33.3 IPS |
|
|
Object Detection (I8)
|
97% |
446
33.3 IPS |
|
|
Face Detection (F32)
|
100% |
929
11.0 IPS |
|
|
Face Detection (F16)
|
100% |
758
9.01 IPS |
|
|
Face Detection (I8)
|
99% |
758
9.01 IPS |
|
|
Depth Estimation (F32)
|
100% |
1496
11.6 IPS |
|
|
Depth Estimation (F16)
|
99% |
1585
12.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
1582
12.3 IPS |
|
|
Style Transfer (F32)
|
100% |
4502
5.92 IPS |
|
|
Style Transfer (F16)
|
100% |
5132
6.75 IPS |
|
|
Style Transfer (I8)
|
100% |
5134
6.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1101
39.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1128
40.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1118
39.9 IPS |
|
|
Text Classification (F32)
|
100% |
443
636.0 IPS |
|
|
Text Classification (F16)
|
100% |
203
292.3 IPS |
|
|
Text Classification (I8)
|
96% |
271
390.2 IPS |
|
|
Machine Translation (F32)
|
100% |
766
14.1 IPS |
|
|
Machine Translation (F16)
|
99% |
932
17.1 IPS |
|
|
Machine Translation (I8)
|
99% |
763
14.0 IPS |
