Nothing A015
Geekbench ML Score
515
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 25 2024 05:30 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Nothing A015 |
| Model ID | Nothing A015 |
| Motherboard | Tetris |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 7.28 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
248
46.4 IPS |
|
|
Image Classification (F16)
|
100% |
251
46.9 IPS |
|
|
Image Classification (I8)
|
97% |
471
88.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
358
5.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
343
5.73 IPS |
|
|
Image Segmentation (I8)
|
98% |
570
9.52 IPS |
|
|
Pose Estimation (F32)
|
100% |
526
0.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
523
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
2335
2.83 IPS |
|
|
Object Detection (F32)
|
100% |
267
19.9 IPS |
|
|
Object Detection (F16)
|
100% |
267
19.9 IPS |
|
|
Object Detection (I8)
|
61% |
497
37.1 IPS |
|
|
Face Detection (F32)
|
100% |
514
6.12 IPS |
|
|
Face Detection (F16)
|
100% |
511
6.07 IPS |
|
|
Face Detection (I8)
|
86% |
1132
13.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
528
4.09 IPS |
|
|
Depth Estimation (F16)
|
100% |
522
4.05 IPS |
|
|
Depth Estimation (I8)
|
95% |
1154
8.95 IPS |
|
|
Style Transfer (F32)
|
100% |
851
1.12 IPS |
|
|
Style Transfer (F16)
|
100% |
858
1.13 IPS |
|
|
Style Transfer (I8)
|
98% |
2497
3.28 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
312
11.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
313
11.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1032
36.9 IPS |
|
|
Text Classification (F32)
|
100% |
342
491.8 IPS |
|
|
Text Classification (F16)
|
100% |
349
501.5 IPS |
|
|
Text Classification (I8)
|
92% |
329
473.5 IPS |
|
|
Machine Translation (F32)
|
100% |
507
9.32 IPS |
|
|
Machine Translation (F16)
|
100% |
507
9.32 IPS |
|
|
Machine Translation (I8)
|
64% |
283
5.20 IPS |
