iPhone 12 Mini
Geekbench ML Score
3889
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 09 2025 08:33 PM |
| Views | 5 |
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% |
392
73.3 IPS |
|
|
Image Classification (F16)
|
100% |
4625
865.4 IPS |
|
|
Image Classification (I8)
|
99% |
4525
846.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
336
5.62 IPS |
|
|
Image Segmentation (F16)
|
100% |
2347
39.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2336
39.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
6127
7.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
58784
71.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
59836
72.5 IPS |
|
|
Object Detection (F32)
|
100% |
598
44.6 IPS |
|
|
Object Detection (F16)
|
100% |
4124
307.9 IPS |
|
|
Object Detection (I8)
|
97% |
580
43.3 IPS |
|
|
Face Detection (F32)
|
100% |
3219
38.3 IPS |
|
|
Face Detection (F16)
|
97% |
9492
112.9 IPS |
|
|
Face Detection (I8)
|
96% |
9126
108.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
5317
41.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
32587
252.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
31213
242.1 IPS |
|
|
Style Transfer (F32)
|
100% |
11712
15.4 IPS |
|
|
Style Transfer (F16)
|
100% |
70504
92.7 IPS |
|
|
Style Transfer (I8)
|
100% |
70584
92.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2059
73.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11852
423.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
12030
429.6 IPS |
|
|
Text Classification (F32)
|
100% |
291
418.9 IPS |
|
|
Text Classification (F16)
|
100% |
794
1.14 KIPS |
|
|
Text Classification (I8)
|
96% |
771
1.11 KIPS |
|
|
Machine Translation (F32)
|
100% |
478
8.80 IPS |
|
|
Machine Translation (F16)
|
100% |
1022
18.8 IPS |
|
|
Machine Translation (I8)
|
99% |
475
8.75 IPS |
