iPhone 12
Geekbench ML Score
3710
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 01 2024 07:38 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 12 |
| Model ID | iPhone13,2 |
| Motherboard | D53gAP |
| 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 | 3.56 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
326
60.9 IPS |
|
|
Image Classification (F16)
|
100% |
4093
765.9 IPS |
|
|
Image Classification (I8)
|
99% |
4598
860.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
495
8.27 IPS |
|
|
Image Segmentation (F16)
|
100% |
3059
51.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
3087
51.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
6124
7.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
61188
74.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
57982
70.2 IPS |
|
|
Object Detection (F32)
|
100% |
591
44.1 IPS |
|
|
Object Detection (F16)
|
100% |
3668
273.9 IPS |
|
|
Object Detection (I8)
|
97% |
577
43.0 IPS |
|
|
Face Detection (F32)
|
100% |
2824
33.6 IPS |
|
|
Face Detection (F16)
|
97% |
10298
122.4 IPS |
|
|
Face Detection (I8)
|
96% |
10221
121.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
3324
25.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
35348
274.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
36687
284.5 IPS |
|
|
Style Transfer (F32)
|
100% |
10363
13.6 IPS |
|
|
Style Transfer (F16)
|
100% |
85135
112.0 IPS |
|
|
Style Transfer (I8)
|
100% |
87747
115.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1387
49.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13023
465.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14730
526.1 IPS |
|
|
Text Classification (F32)
|
100% |
233
334.9 IPS |
|
|
Text Classification (F16)
|
100% |
860
1.24 KIPS |
|
|
Text Classification (I8)
|
96% |
318
457.3 IPS |
|
|
Machine Translation (F32)
|
100% |
311
5.72 IPS |
|
|
Machine Translation (F16)
|
100% |
1139
21.0 IPS |
|
|
Machine Translation (I8)
|
99% |
261
4.80 IPS |
