iPhone 14
Geekbench ML Score
1910
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 17 2024 07:30 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% |
958
179.3 IPS |
|
|
Image Classification (F16)
|
100% |
914
171.1 IPS |
|
|
Image Classification (I8)
|
99% |
914
171.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
625
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
565
9.43 IPS |
|
|
Image Segmentation (I8)
|
100% |
553
9.23 IPS |
|
|
Pose Estimation (F32)
|
100% |
5298
6.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
9612
11.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
9546
11.6 IPS |
|
|
Object Detection (F32)
|
100% |
1019
76.1 IPS |
|
|
Object Detection (F16)
|
100% |
1036
77.4 IPS |
|
|
Object Detection (I8)
|
97% |
1043
77.9 IPS |
|
|
Face Detection (F32)
|
100% |
1708
20.3 IPS |
|
|
Face Detection (F16)
|
100% |
1572
18.7 IPS |
|
|
Face Detection (I8)
|
99% |
1538
18.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
3210
24.9 IPS |
|
|
Depth Estimation (F16)
|
99% |
3692
28.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
3567
27.7 IPS |
|
|
Style Transfer (F32)
|
100% |
9698
12.8 IPS |
|
|
Style Transfer (F16)
|
100% |
11591
15.2 IPS |
|
|
Style Transfer (I8)
|
100% |
11398
15.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2397
85.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2536
90.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2558
91.3 IPS |
|
|
Text Classification (F32)
|
100% |
1000
1.44 KIPS |
|
|
Text Classification (F16)
|
100% |
477
685.4 IPS |
|
|
Text Classification (I8)
|
96% |
641
921.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1349
24.8 IPS |
|
|
Machine Translation (F16)
|
99% |
1722
31.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1325
24.4 IPS |
