iPhone 14
Geekbench ML Score
1933
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 29 2025 01:31 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% |
938
175.5 IPS |
|
|
Image Classification (F16)
|
100% |
915
171.3 IPS |
|
|
Image Classification (I8)
|
99% |
914
171.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
636
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
577
9.63 IPS |
|
|
Image Segmentation (I8)
|
100% |
573
9.57 IPS |
|
|
Pose Estimation (F32)
|
100% |
5455
6.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
9670
11.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
9577
11.6 IPS |
|
|
Object Detection (F32)
|
100% |
1041
77.7 IPS |
|
|
Object Detection (F16)
|
100% |
1043
77.9 IPS |
|
|
Object Detection (I8)
|
97% |
1070
79.8 IPS |
|
|
Face Detection (F32)
|
100% |
1807
21.5 IPS |
|
|
Face Detection (F16)
|
100% |
1605
19.1 IPS |
|
|
Face Detection (I8)
|
99% |
1616
19.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
3260
25.3 IPS |
|
|
Depth Estimation (F16)
|
99% |
3665
28.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
3661
28.4 IPS |
|
|
Style Transfer (F32)
|
100% |
9957
13.1 IPS |
|
|
Style Transfer (F16)
|
100% |
11772
15.5 IPS |
|
|
Style Transfer (I8)
|
100% |
11732
15.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2423
86.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2568
91.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2566
91.6 IPS |
|
|
Text Classification (F32)
|
100% |
987
1.42 KIPS |
|
|
Text Classification (F16)
|
100% |
462
664.2 IPS |
|
|
Text Classification (I8)
|
96% |
610
876.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1358
25.0 IPS |
|
|
Machine Translation (F16)
|
99% |
1767
32.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1337
24.6 IPS |
