iPad mini (6th generation)
Geekbench ML Score
4404
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | suhaasnandeesh |
| Upload Date | May 08 2024 10:27 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPad mini (6th generation) |
| Model ID | iPad14,1 |
| Motherboard | J310AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.92 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 | 3.78 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
604
113.0 IPS |
|
|
Image Classification (F16)
|
100% |
5108
955.9 IPS |
|
|
Image Classification (I8)
|
99% |
5810
1.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1029
17.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1596
26.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1625
27.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
10259
12.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
62381
75.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
63834
77.3 IPS |
|
|
Object Detection (F32)
|
100% |
688
51.4 IPS |
|
|
Object Detection (F16)
|
100% |
3364
251.1 IPS |
|
|
Object Detection (I8)
|
97% |
869
64.8 IPS |
|
|
Face Detection (F32)
|
100% |
3301
39.2 IPS |
|
|
Face Detection (F16)
|
97% |
9276
110.3 IPS |
|
|
Face Detection (I8)
|
96% |
9452
112.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
7347
57.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
32018
248.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
37480
290.7 IPS |
|
|
Style Transfer (F32)
|
100% |
18400
24.2 IPS |
|
|
Style Transfer (F16)
|
100% |
95205
125.2 IPS |
|
|
Style Transfer (I8)
|
100% |
94929
124.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2474
88.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14090
503.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14542
519.3 IPS |
|
|
Text Classification (F32)
|
100% |
373
536.0 IPS |
|
|
Text Classification (F16)
|
100% |
816
1.17 KIPS |
|
|
Text Classification (I8)
|
96% |
369
530.2 IPS |
|
|
Machine Translation (F32)
|
100% |
449
8.26 IPS |
|
|
Machine Translation (F16)
|
100% |
1185
21.8 IPS |
|
|
Machine Translation (I8)
|
99% |
411
7.56 IPS |
