iPhone 12 Mini
Geekbench ML Score
3919
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 09 2025 04:36 AM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.1.1 |
| 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 | 3.60 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
352
65.9 IPS |
|
|
Image Classification (F16)
|
100% |
4782
894.9 IPS |
|
|
Image Classification (I8)
|
99% |
4513
844.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
330
5.51 IPS |
|
|
Image Segmentation (F16)
|
100% |
2548
42.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
2578
43.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
6155
7.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
59211
71.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
57604
69.8 IPS |
|
|
Object Detection (F32)
|
100% |
610
45.5 IPS |
|
|
Object Detection (F16)
|
100% |
4258
317.9 IPS |
|
|
Object Detection (I8)
|
97% |
631
47.1 IPS |
|
|
Face Detection (F32)
|
100% |
3170
37.7 IPS |
|
|
Face Detection (F16)
|
97% |
9442
112.3 IPS |
|
|
Face Detection (I8)
|
96% |
9108
108.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
5222
40.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
32220
249.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
30956
240.1 IPS |
|
|
Style Transfer (F32)
|
100% |
11769
15.5 IPS |
|
|
Style Transfer (F16)
|
100% |
72804
95.8 IPS |
|
|
Style Transfer (I8)
|
100% |
73289
96.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1951
69.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11747
419.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11787
420.9 IPS |
|
|
Text Classification (F32)
|
100% |
281
404.3 IPS |
|
|
Text Classification (F16)
|
100% |
823
1.18 KIPS |
|
|
Text Classification (I8)
|
96% |
822
1.18 KIPS |
|
|
Machine Translation (F32)
|
100% |
480
8.83 IPS |
|
|
Machine Translation (F16)
|
100% |
1038
19.1 IPS |
|
|
Machine Translation (I8)
|
99% |
484
8.92 IPS |
