Alldocube iPlay60_mini_Pro
Geekbench ML Score
363
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 29 2024 04:32 AM |
| Views | 1 |
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% |
168
31.4 IPS |
|
|
Image Classification (F16)
|
100% |
168
31.5 IPS |
|
|
Image Classification (I8)
|
97% |
298
55.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
262
4.37 IPS |
|
|
Image Segmentation (F16)
|
100% |
259
4.33 IPS |
|
|
Image Segmentation (I8)
|
98% |
403
6.73 IPS |
|
|
Pose Estimation (F32)
|
100% |
332
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
317
0.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
1695
2.05 IPS |
|
|
Object Detection (F32)
|
100% |
205
15.3 IPS |
|
|
Object Detection (F16)
|
100% |
205
15.3 IPS |
|
|
Object Detection (I8)
|
61% |
388
29.0 IPS |
|
|
Face Detection (F32)
|
100% |
388
4.61 IPS |
|
|
Face Detection (F16)
|
100% |
382
4.55 IPS |
|
|
Face Detection (I8)
|
86% |
878
10.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
358
2.78 IPS |
|
|
Depth Estimation (F16)
|
100% |
362
2.81 IPS |
|
|
Depth Estimation (I8)
|
95% |
861
6.68 IPS |
|
|
Style Transfer (F32)
|
100% |
547
0.72 IPS |
|
|
Style Transfer (F16)
|
100% |
553
0.73 IPS |
|
|
Style Transfer (I8)
|
98% |
1825
2.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
220
7.86 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
210
7.50 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
664
23.7 IPS |
|
|
Text Classification (F32)
|
100% |
236
338.6 IPS |
|
|
Text Classification (F16)
|
100% |
211
302.8 IPS |
|
|
Text Classification (I8)
|
92% |
182
262.1 IPS |
|
|
Machine Translation (F32)
|
100% |
419
7.72 IPS |
|
|
Machine Translation (F16)
|
100% |
423
7.78 IPS |
|
|
Machine Translation (I8)
|
64% |
256
4.70 IPS |
