iPhone 14
Geekbench ML Score
1746
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 11 2025 06:24 PM |
| Views | 3 |
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% |
763
142.7 IPS |
|
|
Image Classification (F16)
|
100% |
715
133.7 IPS |
|
|
Image Classification (I8)
|
99% |
698
130.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
451
7.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
404
6.75 IPS |
|
|
Image Segmentation (I8)
|
100% |
469
7.83 IPS |
|
|
Pose Estimation (F32)
|
100% |
4936
5.98 IPS |
|
|
Pose Estimation (F16)
|
100% |
9007
10.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
9041
10.9 IPS |
|
|
Object Detection (F32)
|
100% |
992
74.0 IPS |
|
|
Object Detection (F16)
|
100% |
985
73.5 IPS |
|
|
Object Detection (I8)
|
97% |
981
73.3 IPS |
|
|
Face Detection (F32)
|
100% |
1632
19.4 IPS |
|
|
Face Detection (F16)
|
100% |
1461
17.4 IPS |
|
|
Face Detection (I8)
|
99% |
1457
17.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
3072
23.8 IPS |
|
|
Depth Estimation (F16)
|
99% |
3475
27.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
3374
26.2 IPS |
|
|
Style Transfer (F32)
|
100% |
9106
12.0 IPS |
|
|
Style Transfer (F16)
|
100% |
10852
14.3 IPS |
|
|
Style Transfer (I8)
|
100% |
10907
14.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2299
82.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2504
89.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2521
90.0 IPS |
|
|
Text Classification (F32)
|
100% |
988
1.42 KIPS |
|
|
Text Classification (F16)
|
100% |
459
659.7 IPS |
|
|
Text Classification (I8)
|
96% |
626
899.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1273
23.4 IPS |
|
|
Machine Translation (F16)
|
99% |
1653
30.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1261
23.2 IPS |
