Nothing A015
Geekbench ML Score
318
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 25 2024 05:43 PM |
| Views | 2 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
185
34.5 IPS |
|
|
Image Classification (F16)
|
100% |
251
47.0 IPS |
|
|
Image Classification (I8)
|
97% |
216
40.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
365
6.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
423
7.06 IPS |
|
|
Image Segmentation (I8)
|
98% |
412
6.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
185
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
245
0.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
244
0.30 IPS |
|
|
Object Detection (F32)
|
100% |
171
12.8 IPS |
|
|
Object Detection (F16)
|
100% |
205
15.3 IPS |
|
|
Object Detection (I8)
|
62% |
219
16.3 IPS |
|
|
Face Detection (F32)
|
100% |
702
8.34 IPS |
|
|
Face Detection (F16)
|
98% |
770
9.16 IPS |
|
|
Face Detection (I8)
|
86% |
748
8.89 IPS |
|
|
Depth Estimation (F32)
|
100% |
386
3.00 IPS |
|
|
Depth Estimation (F16)
|
100% |
483
3.75 IPS |
|
|
Depth Estimation (I8)
|
95% |
479
3.71 IPS |
|
|
Style Transfer (F32)
|
100% |
979
1.29 IPS |
|
|
Style Transfer (F16)
|
100% |
1164
1.53 IPS |
|
|
Style Transfer (I8)
|
98% |
1162
1.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
223
7.98 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
253
9.02 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
252
8.99 IPS |
|
|
Text Classification (F32)
|
100% |
108
154.6 IPS |
|
|
Text Classification (F16)
|
100% |
107
153.6 IPS |
|
|
Text Classification (I8)
|
92% |
269
387.3 IPS |
|
|
Machine Translation (F32)
|
100% |
191
3.51 IPS |
|
|
Machine Translation (F16)
|
100% |
192
3.54 IPS |
|
|
Machine Translation (I8)
|
64% |
304
5.60 IPS |
