Alldocube iPlay60_mini_Pro
Geekbench ML Score
367
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 19 2024 01:59 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Alldocube iPlay60_mini_Pro |
| Model ID | Alldocube iPlay60_mini_Pro |
| Motherboard | tb8781p1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.54 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
155
29.0 IPS |
|
|
Image Classification (F16)
|
100% |
170
31.8 IPS |
|
|
Image Classification (I8)
|
97% |
325
60.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
268
4.48 IPS |
|
|
Image Segmentation (F16)
|
100% |
273
4.56 IPS |
|
|
Image Segmentation (I8)
|
98% |
414
6.91 IPS |
|
|
Pose Estimation (F32)
|
100% |
331
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
337
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1673
2.03 IPS |
|
|
Object Detection (F32)
|
100% |
207
15.5 IPS |
|
|
Object Detection (F16)
|
100% |
208
15.5 IPS |
|
|
Object Detection (I8)
|
61% |
384
28.7 IPS |
|
|
Face Detection (F32)
|
100% |
386
4.59 IPS |
|
|
Face Detection (F16)
|
100% |
385
4.58 IPS |
|
|
Face Detection (I8)
|
86% |
848
10.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
365
2.83 IPS |
|
|
Depth Estimation (F16)
|
100% |
367
2.85 IPS |
|
|
Depth Estimation (I8)
|
95% |
858
6.65 IPS |
|
|
Style Transfer (F32)
|
100% |
554
0.73 IPS |
|
|
Style Transfer (F16)
|
100% |
554
0.73 IPS |
|
|
Style Transfer (I8)
|
98% |
1839
2.42 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
218
7.79 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
218
7.77 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
677
24.2 IPS |
|
|
Text Classification (F32)
|
100% |
227
325.8 IPS |
|
|
Text Classification (F16)
|
100% |
227
326.0 IPS |
|
|
Text Classification (I8)
|
92% |
178
255.9 IPS |
|
|
Machine Translation (F32)
|
100% |
427
7.86 IPS |
|
|
Machine Translation (F16)
|
100% |
425
7.81 IPS |
|
|
Machine Translation (I8)
|
64% |
252
4.64 IPS |
