iPhone 12
Geekbench ML Score
1613
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | February 12 2024 06:55 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.6 |
| 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 | 3.58 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
762
142.5 IPS |
|
|
Image Classification (F16)
|
100% |
759
142.1 IPS |
|
|
Image Classification (I8)
|
99% |
761
142.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
551
9.21 IPS |
|
|
Image Segmentation (F16)
|
100% |
504
8.43 IPS |
|
|
Image Segmentation (I8)
|
100% |
502
8.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
4769
5.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
7825
9.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
7772
9.41 IPS |
|
|
Object Detection (F32)
|
100% |
791
59.1 IPS |
|
|
Object Detection (F16)
|
100% |
860
64.2 IPS |
|
|
Object Detection (I8)
|
97% |
793
59.2 IPS |
|
|
Face Detection (F32)
|
100% |
1436
17.1 IPS |
|
|
Face Detection (F16)
|
100% |
1349
16.0 IPS |
|
|
Face Detection (I8)
|
99% |
1331
15.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
2819
21.9 IPS |
|
|
Depth Estimation (F16)
|
99% |
3142
24.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
3174
24.6 IPS |
|
|
Style Transfer (F32)
|
100% |
8612
11.3 IPS |
|
|
Style Transfer (F16)
|
100% |
9993
13.1 IPS |
|
|
Style Transfer (I8)
|
100% |
9860
13.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2022
72.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2209
78.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2208
78.8 IPS |
|
|
Text Classification (F32)
|
100% |
823
1.18 KIPS |
|
|
Text Classification (F16)
|
100% |
396
568.9 IPS |
|
|
Text Classification (I8)
|
96% |
516
741.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1102
20.3 IPS |
|
|
Machine Translation (F16)
|
99% |
1460
26.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1081
19.9 IPS |
