iPhone 12
Geekbench ML Score
3918
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 25 2024 12:01 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
314
58.7 IPS |
|
|
Image Classification (F16)
|
100% |
4197
785.4 IPS |
|
|
Image Classification (I8)
|
99% |
5275
987.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
547
9.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
3170
52.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
3124
52.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
5784
7.00 IPS |
|
|
Pose Estimation (F16)
|
100% |
56746
68.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
60143
72.8 IPS |
|
|
Object Detection (F32)
|
100% |
591
44.1 IPS |
|
|
Object Detection (F16)
|
100% |
3647
272.3 IPS |
|
|
Object Detection (I8)
|
97% |
579
43.2 IPS |
|
|
Face Detection (F32)
|
100% |
2822
33.6 IPS |
|
|
Face Detection (F16)
|
97% |
10277
122.2 IPS |
|
|
Face Detection (I8)
|
96% |
10264
122.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5404
41.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
32525
252.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
34780
269.7 IPS |
|
|
Style Transfer (F32)
|
100% |
10978
14.4 IPS |
|
|
Style Transfer (F16)
|
100% |
92418
121.6 IPS |
|
|
Style Transfer (I8)
|
100% |
95827
126.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1976
70.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15195
542.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15263
545.1 IPS |
|
|
Text Classification (F32)
|
100% |
257
368.8 IPS |
|
|
Text Classification (F16)
|
100% |
894
1.28 KIPS |
|
|
Text Classification (I8)
|
96% |
328
470.7 IPS |
|
|
Machine Translation (F32)
|
100% |
324
5.96 IPS |
|
|
Machine Translation (F16)
|
100% |
1020
18.8 IPS |
|
|
Machine Translation (I8)
|
99% |
333
6.12 IPS |
