iPhone 13 mini
Geekbench ML Score
1762
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 21 2024 01:41 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.2.1 |
| Model | iPhone 13 mini |
| Model ID | iPhone14,4 |
| Motherboard | D16AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 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 | 3.57 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
941
176.0 IPS |
|
|
Image Classification (F16)
|
100% |
893
167.1 IPS |
|
|
Image Classification (I8)
|
99% |
905
169.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
490
8.18 IPS |
|
|
Image Segmentation (F16)
|
100% |
456
7.61 IPS |
|
|
Image Segmentation (I8)
|
100% |
441
7.37 IPS |
|
|
Pose Estimation (F32)
|
100% |
5249
6.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
10192
12.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
10103
12.2 IPS |
|
|
Object Detection (F32)
|
100% |
949
70.8 IPS |
|
|
Object Detection (F16)
|
100% |
997
74.4 IPS |
|
|
Object Detection (I8)
|
97% |
981
73.2 IPS |
|
|
Face Detection (F32)
|
100% |
1634
19.4 IPS |
|
|
Face Detection (F16)
|
100% |
1537
18.3 IPS |
|
|
Face Detection (I8)
|
99% |
1501
17.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
3333
25.8 IPS |
|
|
Depth Estimation (F16)
|
99% |
3679
28.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
3642
28.2 IPS |
|
|
Style Transfer (F32)
|
100% |
9828
12.9 IPS |
|
|
Style Transfer (F16)
|
100% |
11401
15.0 IPS |
|
|
Style Transfer (I8)
|
100% |
11590
15.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2864
102.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2615
93.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2547
90.9 IPS |
|
|
Text Classification (F32)
|
100% |
961
1.38 KIPS |
|
|
Text Classification (F16)
|
100% |
592
850.1 IPS |
|
|
Text Classification (I8)
|
96% |
582
835.8 IPS |
|
|
Machine Translation (F32)
|
100% |
754
13.9 IPS |
|
|
Machine Translation (F16)
|
99% |
850
15.6 IPS |
|
|
Machine Translation (I8)
|
99% |
725
13.3 IPS |
