iPhone 13 mini
Geekbench ML Score
4884
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 19 2024 01:52 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.4.1 |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
496
92.8 IPS |
|
|
Image Classification (F16)
|
100% |
5277
987.4 IPS |
|
|
Image Classification (I8)
|
99% |
5441
1.02 KIPS |
|
|
Image Segmentation (F32)
|
100% |
544
9.08 IPS |
|
|
Image Segmentation (F16)
|
100% |
3016
50.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
3101
51.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
9096
11.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
75831
91.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
79943
96.8 IPS |
|
|
Object Detection (F32)
|
100% |
1084
81.0 IPS |
|
|
Object Detection (F16)
|
100% |
3810
284.4 IPS |
|
|
Object Detection (I8)
|
97% |
1166
87.0 IPS |
|
|
Face Detection (F32)
|
100% |
4188
49.8 IPS |
|
|
Face Detection (F16)
|
97% |
9521
113.2 IPS |
|
|
Face Detection (I8)
|
96% |
10883
129.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
7714
59.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
29421
228.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
28734
222.8 IPS |
|
|
Style Transfer (F32)
|
100% |
16574
21.8 IPS |
|
|
Style Transfer (F16)
|
100% |
88351
116.2 IPS |
|
|
Style Transfer (I8)
|
100% |
92013
121.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2717
97.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11733
419.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
13225
472.3 IPS |
|
|
Text Classification (F32)
|
100% |
403
579.7 IPS |
|
|
Text Classification (F16)
|
100% |
849
1.22 KIPS |
|
|
Text Classification (I8)
|
96% |
851
1.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
628
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1134
20.9 IPS |
|
|
Machine Translation (I8)
|
99% |
722
13.3 IPS |
