iPhone 14
Geekbench ML Score
1935
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | February 16 2025 11:41 PM |
| Views | 4 |
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% |
944
176.6 IPS |
|
|
Image Classification (F16)
|
100% |
909
170.2 IPS |
|
|
Image Classification (I8)
|
99% |
913
170.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
638
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
577
9.63 IPS |
|
|
Image Segmentation (I8)
|
100% |
569
9.50 IPS |
|
|
Pose Estimation (F32)
|
100% |
5527
6.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
9572
11.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
9571
11.6 IPS |
|
|
Object Detection (F32)
|
100% |
1064
79.4 IPS |
|
|
Object Detection (F16)
|
100% |
1050
78.4 IPS |
|
|
Object Detection (I8)
|
97% |
1031
76.9 IPS |
|
|
Face Detection (F32)
|
100% |
1796
21.4 IPS |
|
|
Face Detection (F16)
|
100% |
1617
19.2 IPS |
|
|
Face Detection (I8)
|
99% |
1597
19.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3312
25.7 IPS |
|
|
Depth Estimation (F16)
|
99% |
3651
28.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
3685
28.6 IPS |
|
|
Style Transfer (F32)
|
100% |
9959
13.1 IPS |
|
|
Style Transfer (F16)
|
100% |
11804
15.5 IPS |
|
|
Style Transfer (I8)
|
100% |
11772
15.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2427
86.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2567
91.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2565
91.6 IPS |
|
|
Text Classification (F32)
|
100% |
992
1.43 KIPS |
|
|
Text Classification (F16)
|
100% |
465
668.1 IPS |
|
|
Text Classification (I8)
|
96% |
618
888.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1354
24.9 IPS |
|
|
Machine Translation (F16)
|
99% |
1759
32.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1342
24.7 IPS |
