iPhone 12 Pro
Geekbench ML Score
734
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 27 2024 07:28 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 12 Pro |
| Model ID | iPhone13,3 |
| Motherboard | D53pAP |
| 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 | 5.58 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
187
35.0 IPS |
|
|
Image Classification (F16)
|
100% |
377
70.5 IPS |
|
|
Image Classification (I8)
|
99% |
382
71.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
92
1.54 IPS |
|
|
Image Segmentation (F16)
|
100% |
121
2.01 IPS |
|
|
Image Segmentation (I8)
|
100% |
128
2.13 IPS |
|
|
Pose Estimation (F32)
|
100% |
669
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
2076
2.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
1615
1.96 IPS |
|
|
Object Detection (F32)
|
100% |
376
28.1 IPS |
|
|
Object Detection (F16)
|
100% |
607
45.3 IPS |
|
|
Object Detection (I8)
|
97% |
409
30.5 IPS |
|
|
Face Detection (F32)
|
100% |
756
8.98 IPS |
|
|
Face Detection (F16)
|
97% |
1216
14.5 IPS |
|
|
Face Detection (I8)
|
97% |
1189
14.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1261
9.78 IPS |
|
|
Depth Estimation (F16)
|
100% |
2510
19.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
2445
19.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2429
3.19 IPS |
|
|
Style Transfer (F16)
|
100% |
4970
6.54 IPS |
|
|
Style Transfer (I8)
|
100% |
5005
6.58 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1082
38.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1486
53.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1492
53.3 IPS |
|
|
Text Classification (F32)
|
100% |
619
889.7 IPS |
|
|
Text Classification (F16)
|
100% |
1197
1.72 KIPS |
|
|
Text Classification (I8)
|
96% |
1616
2.32 KIPS |
|
|
Machine Translation (F32)
|
100% |
183
3.36 IPS |
|
|
Machine Translation (F16)
|
100% |
246
4.52 IPS |
|
|
Machine Translation (I8)
|
99% |
182
3.34 IPS |
