iPhone 13 mini
Geekbench ML Score
3297
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 26 2024 04:35 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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 | 3.55 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1388
259.8 IPS |
|
|
Image Classification (F16)
|
100% |
1731
323.9 IPS |
|
|
Image Classification (I8)
|
99% |
1750
327.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
847
14.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
818
13.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
817
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
5822
7.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
13468
16.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
13424
16.3 IPS |
|
|
Object Detection (F32)
|
100% |
1374
102.5 IPS |
|
|
Object Detection (F16)
|
100% |
1846
137.8 IPS |
|
|
Object Detection (I8)
|
97% |
1371
102.3 IPS |
|
|
Face Detection (F32)
|
100% |
2460
29.2 IPS |
|
|
Face Detection (F16)
|
97% |
3934
46.8 IPS |
|
|
Face Detection (I8)
|
97% |
3938
46.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
4999
38.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8159
63.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
8105
62.9 IPS |
|
|
Style Transfer (F32)
|
100% |
16185
21.3 IPS |
|
|
Style Transfer (F16)
|
100% |
24959
32.8 IPS |
|
|
Style Transfer (I8)
|
100% |
24944
32.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3678
131.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4847
173.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4835
172.7 IPS |
|
|
Text Classification (F32)
|
100% |
2186
3.14 KIPS |
|
|
Text Classification (F16)
|
100% |
3092
4.44 KIPS |
|
|
Text Classification (I8)
|
96% |
3079
4.43 KIPS |
|
|
Machine Translation (F32)
|
100% |
1154
21.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1391
25.6 IPS |
|
|
Machine Translation (I8)
|
99% |
1103
20.3 IPS |
