iPhone 14
Geekbench ML Score
1807
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | March 28 2025 02:46 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% |
878
164.3 IPS |
|
|
Image Classification (F16)
|
100% |
829
155.1 IPS |
|
|
Image Classification (I8)
|
99% |
825
154.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
556
9.29 IPS |
|
|
Image Segmentation (F16)
|
100% |
495
8.26 IPS |
|
|
Image Segmentation (I8)
|
100% |
493
8.24 IPS |
|
|
Pose Estimation (F32)
|
100% |
4928
5.97 IPS |
|
|
Pose Estimation (F16)
|
100% |
9275
11.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
8989
10.9 IPS |
|
|
Object Detection (F32)
|
100% |
973
72.7 IPS |
|
|
Object Detection (F16)
|
100% |
987
73.7 IPS |
|
|
Object Detection (I8)
|
97% |
963
71.9 IPS |
|
|
Face Detection (F32)
|
100% |
1663
19.8 IPS |
|
|
Face Detection (F16)
|
100% |
1465
17.4 IPS |
|
|
Face Detection (I8)
|
99% |
1453
17.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
3035
23.5 IPS |
|
|
Depth Estimation (F16)
|
99% |
3535
27.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
3394
26.3 IPS |
|
|
Style Transfer (F32)
|
100% |
9280
12.2 IPS |
|
|
Style Transfer (F16)
|
100% |
11065
14.6 IPS |
|
|
Style Transfer (I8)
|
100% |
11150
14.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2310
82.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2523
90.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2459
87.8 IPS |
|
|
Text Classification (F32)
|
100% |
983
1.41 KIPS |
|
|
Text Classification (F16)
|
100% |
463
665.7 IPS |
|
|
Text Classification (I8)
|
96% |
608
874.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1311
24.1 IPS |
|
|
Machine Translation (F16)
|
99% |
1677
30.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1290
23.7 IPS |
