iPhone 12 Pro Max
Geekbench ML Score
3589
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 25 2024 10:31 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.0.3 |
| Model | iPhone 12 Pro Max |
| Model ID | iPhone13,4 |
| Motherboard | D54pAP |
| CPU Information | |
|---|---|
| Name | Apple A14 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.99 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 | 5.54 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
351
65.7 IPS |
|
|
Image Classification (F16)
|
100% |
4087
764.9 IPS |
|
|
Image Classification (I8)
|
99% |
4154
777.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
322
5.38 IPS |
|
|
Image Segmentation (F16)
|
100% |
1444
24.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1412
23.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
6119
7.41 IPS |
|
|
Pose Estimation (F16)
|
100% |
54893
66.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
59596
72.2 IPS |
|
|
Object Detection (F32)
|
100% |
589
43.9 IPS |
|
|
Object Detection (F16)
|
100% |
3773
281.6 IPS |
|
|
Object Detection (I8)
|
97% |
543
40.5 IPS |
|
|
Face Detection (F32)
|
100% |
3221
38.3 IPS |
|
|
Face Detection (F16)
|
97% |
7405
88.1 IPS |
|
|
Face Detection (I8)
|
96% |
7431
88.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
5203
40.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
30027
232.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
29899
231.9 IPS |
|
|
Style Transfer (F32)
|
100% |
10966
14.4 IPS |
|
|
Style Transfer (F16)
|
100% |
69607
91.6 IPS |
|
|
Style Transfer (I8)
|
100% |
70202
92.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1942
69.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11643
415.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11501
410.7 IPS |
|
|
Text Classification (F32)
|
100% |
281
404.3 IPS |
|
|
Text Classification (F16)
|
100% |
793
1.14 KIPS |
|
|
Text Classification (I8)
|
96% |
810
1.16 KIPS |
|
|
Machine Translation (F32)
|
100% |
479
8.81 IPS |
|
|
Machine Translation (F16)
|
100% |
991
18.2 IPS |
|
|
Machine Translation (I8)
|
99% |
479
8.82 IPS |
