Nothing A065
Geekbench ML Score
743
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 12 2024 06:55 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Nothing A065 |
| Model ID | Nothing A065 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 11.00 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
485
90.8 IPS |
|
|
Image Classification (F16)
|
100% |
855
159.9 IPS |
|
|
Image Classification (I8)
|
97% |
379
70.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
742
12.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
899
15.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
844
14.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
668
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
1215
1.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
1208
1.46 IPS |
|
|
Object Detection (F32)
|
100% |
284
21.2 IPS |
|
|
Object Detection (F16)
|
100% |
247
18.5 IPS |
|
|
Object Detection (I8)
|
62% |
243
18.1 IPS |
|
|
Face Detection (F32)
|
100% |
1427
17.0 IPS |
|
|
Face Detection (F16)
|
97% |
1463
17.4 IPS |
|
|
Face Detection (I8)
|
87% |
1387
16.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1053
8.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
2314
17.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2301
17.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2565
3.37 IPS |
|
|
Style Transfer (F16)
|
100% |
4776
6.28 IPS |
|
|
Style Transfer (I8)
|
98% |
5682
7.47 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
375
13.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
485
17.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
388
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
210
302.0 IPS |
|
|
Text Classification (F16)
|
100% |
210
302.4 IPS |
|
|
Text Classification (I8)
|
92% |
382
548.4 IPS |
|
|
Machine Translation (F32)
|
100% |
387
7.13 IPS |
|
|
Machine Translation (F16)
|
100% |
388
7.14 IPS |
|
|
Machine Translation (I8)
|
64% |
470
8.65 IPS |
