iPhone 12 Mini
Geekbench ML Score
4051
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 07:10 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.2 |
| Model | iPhone 12 Mini |
| Model ID | iPhone13,1 |
| Motherboard | D52gAP |
| 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 | 3.60 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
375
70.2 IPS |
|
|
Image Classification (F16)
|
100% |
5251
982.7 IPS |
|
|
Image Classification (I8)
|
99% |
5365
1.00 KIPS |
|
|
Image Segmentation (F32)
|
100% |
339
5.67 IPS |
|
|
Image Segmentation (F16)
|
100% |
2394
40.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
2422
40.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
6173
7.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
61094
74.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
59715
72.3 IPS |
|
|
Object Detection (F32)
|
100% |
612
45.7 IPS |
|
|
Object Detection (F16)
|
100% |
4261
318.1 IPS |
|
|
Object Detection (I8)
|
97% |
632
47.2 IPS |
|
|
Face Detection (F32)
|
100% |
3240
38.5 IPS |
|
|
Face Detection (F16)
|
97% |
9668
115.0 IPS |
|
|
Face Detection (I8)
|
96% |
9597
114.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
5346
41.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
32245
250.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
33319
258.4 IPS |
|
|
Style Transfer (F32)
|
100% |
11709
15.4 IPS |
|
|
Style Transfer (F16)
|
100% |
76679
100.9 IPS |
|
|
Style Transfer (I8)
|
100% |
78481
103.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1998
71.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12614
450.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
12500
446.4 IPS |
|
|
Text Classification (F32)
|
100% |
307
441.4 IPS |
|
|
Text Classification (F16)
|
100% |
858
1.23 KIPS |
|
|
Text Classification (I8)
|
96% |
865
1.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
497
9.14 IPS |
|
|
Machine Translation (F16)
|
100% |
1031
19.0 IPS |
|
|
Machine Translation (I8)
|
99% |
489
9.00 IPS |
