iPhone 13 mini
Geekbench ML Score
4624
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 11:56 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
850
159.1 IPS |
|
|
Image Classification (F16)
|
100% |
5034
941.9 IPS |
|
|
Image Classification (I8)
|
99% |
5877
1.10 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1191
19.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1732
28.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1715
28.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
8948
10.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
73509
89.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
73729
89.3 IPS |
|
|
Object Detection (F32)
|
100% |
1034
77.2 IPS |
|
|
Object Detection (F16)
|
100% |
3415
255.0 IPS |
|
|
Object Detection (I8)
|
97% |
956
71.4 IPS |
|
|
Face Detection (F32)
|
100% |
3821
45.4 IPS |
|
|
Face Detection (F16)
|
97% |
9977
118.6 IPS |
|
|
Face Detection (I8)
|
96% |
9853
117.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
5564
43.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
32125
249.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
37546
291.2 IPS |
|
|
Style Transfer (F32)
|
100% |
16700
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
97678
128.5 IPS |
|
|
Style Transfer (I8)
|
100% |
99193
130.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2587
92.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14332
511.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15076
538.4 IPS |
|
|
Text Classification (F32)
|
100% |
371
533.3 IPS |
|
|
Text Classification (F16)
|
100% |
829
1.19 KIPS |
|
|
Text Classification (I8)
|
96% |
329
473.1 IPS |
|
|
Machine Translation (F32)
|
100% |
495
9.12 IPS |
|
|
Machine Translation (F16)
|
100% |
1145
21.1 IPS |
|
|
Machine Translation (I8)
|
99% |
470
8.65 IPS |
