iPhone 12 Mini
Geekbench ML Score
3881
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 07 2024 01:50 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 3.57 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
319
59.7 IPS |
|
|
Image Classification (F16)
|
100% |
3581
670.0 IPS |
|
|
Image Classification (I8)
|
99% |
4695
878.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
542
9.05 IPS |
|
|
Image Segmentation (F16)
|
100% |
3279
54.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
3277
54.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
5829
7.06 IPS |
|
|
Pose Estimation (F16)
|
100% |
61551
74.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
58395
70.7 IPS |
|
|
Object Detection (F32)
|
100% |
593
44.3 IPS |
|
|
Object Detection (F16)
|
100% |
3405
254.2 IPS |
|
|
Object Detection (I8)
|
97% |
532
39.7 IPS |
|
|
Face Detection (F32)
|
100% |
2732
32.5 IPS |
|
|
Face Detection (F16)
|
97% |
10290
122.3 IPS |
|
|
Face Detection (I8)
|
96% |
10262
122.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5370
41.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
33659
261.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
35187
272.9 IPS |
|
|
Style Transfer (F32)
|
100% |
10586
13.9 IPS |
|
|
Style Transfer (F16)
|
100% |
94078
123.8 IPS |
|
|
Style Transfer (I8)
|
100% |
98652
129.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1862
66.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15383
549.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15474
552.6 IPS |
|
|
Text Classification (F32)
|
100% |
254
364.6 IPS |
|
|
Text Classification (F16)
|
100% |
898
1.29 KIPS |
|
|
Text Classification (I8)
|
96% |
327
470.5 IPS |
|
|
Machine Translation (F32)
|
100% |
331
6.09 IPS |
|
|
Machine Translation (F16)
|
100% |
1023
18.8 IPS |
|
|
Machine Translation (I8)
|
99% |
331
6.09 IPS |
