iPhone 14
Geekbench ML Score
1880
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 13 2025 05:43 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% |
931
174.2 IPS |
|
|
Image Classification (F16)
|
100% |
887
166.0 IPS |
|
|
Image Classification (I8)
|
99% |
909
170.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
616
10.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
532
8.89 IPS |
|
|
Image Segmentation (I8)
|
100% |
529
8.83 IPS |
|
|
Pose Estimation (F32)
|
100% |
5245
6.35 IPS |
|
|
Pose Estimation (F16)
|
100% |
9555
11.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
9450
11.4 IPS |
|
|
Object Detection (F32)
|
100% |
1026
76.6 IPS |
|
|
Object Detection (F16)
|
100% |
1028
76.7 IPS |
|
|
Object Detection (I8)
|
97% |
1012
75.5 IPS |
|
|
Face Detection (F32)
|
100% |
1712
20.4 IPS |
|
|
Face Detection (F16)
|
100% |
1521
18.1 IPS |
|
|
Face Detection (I8)
|
99% |
1501
17.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
3140
24.4 IPS |
|
|
Depth Estimation (F16)
|
99% |
3658
28.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
3490
27.1 IPS |
|
|
Style Transfer (F32)
|
100% |
9591
12.6 IPS |
|
|
Style Transfer (F16)
|
100% |
11199
14.7 IPS |
|
|
Style Transfer (I8)
|
100% |
11340
14.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2354
84.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2542
90.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2564
91.6 IPS |
|
|
Text Classification (F32)
|
100% |
997
1.43 KIPS |
|
|
Text Classification (F16)
|
100% |
462
664.5 IPS |
|
|
Text Classification (I8)
|
96% |
641
921.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1337
24.6 IPS |
|
|
Machine Translation (F16)
|
99% |
1707
31.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1308
24.1 IPS |
