Nothing A015
Geekbench ML Score
514
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 25 2024 05:25 PM |
| Views | 3 |
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% |
243
45.6 IPS |
|
|
Image Classification (F16)
|
100% |
248
46.4 IPS |
|
|
Image Classification (I8)
|
97% |
463
86.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
346
5.79 IPS |
|
|
Image Segmentation (F16)
|
100% |
348
5.81 IPS |
|
|
Image Segmentation (I8)
|
98% |
568
9.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
525
0.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
526
0.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
2300
2.79 IPS |
|
|
Object Detection (F32)
|
100% |
271
20.2 IPS |
|
|
Object Detection (F16)
|
100% |
264
19.7 IPS |
|
|
Object Detection (I8)
|
61% |
520
38.8 IPS |
|
|
Face Detection (F32)
|
100% |
521
6.19 IPS |
|
|
Face Detection (F16)
|
100% |
517
6.14 IPS |
|
|
Face Detection (I8)
|
86% |
1135
13.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
535
4.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
530
4.11 IPS |
|
|
Depth Estimation (I8)
|
95% |
1118
8.67 IPS |
|
|
Style Transfer (F32)
|
100% |
869
1.14 IPS |
|
|
Style Transfer (F16)
|
100% |
865
1.14 IPS |
|
|
Style Transfer (I8)
|
98% |
2489
3.27 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
304
10.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
308
11.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
982
35.1 IPS |
|
|
Text Classification (F32)
|
100% |
348
500.1 IPS |
|
|
Text Classification (F16)
|
100% |
344
494.3 IPS |
|
|
Text Classification (I8)
|
92% |
326
468.3 IPS |
|
|
Machine Translation (F32)
|
100% |
520
9.57 IPS |
|
|
Machine Translation (F16)
|
100% |
510
9.38 IPS |
|
|
Machine Translation (I8)
|
64% |
286
5.27 IPS |
