Nothing A065
Geekbench ML Score
406
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 02:20 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
197
36.9 IPS |
|
|
Image Classification (F16)
|
100% |
197
36.8 IPS |
|
|
Image Classification (I8)
|
97% |
547
102.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
250
4.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
250
4.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
578
9.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
331
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
336
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1356
1.64 IPS |
|
|
Object Detection (F32)
|
100% |
206
15.4 IPS |
|
|
Object Detection (F16)
|
100% |
206
15.4 IPS |
|
|
Object Detection (I8)
|
61% |
597
44.6 IPS |
|
|
Face Detection (F32)
|
100% |
536
6.38 IPS |
|
|
Face Detection (F16)
|
100% |
535
6.36 IPS |
|
|
Face Detection (I8)
|
86% |
1180
14.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
354
2.75 IPS |
|
|
Depth Estimation (F16)
|
100% |
355
2.75 IPS |
|
|
Depth Estimation (I8)
|
95% |
1029
7.98 IPS |
|
|
Style Transfer (F32)
|
100% |
621
0.82 IPS |
|
|
Style Transfer (F16)
|
100% |
630
0.83 IPS |
|
|
Style Transfer (I8)
|
98% |
1555
2.04 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
181
6.46 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
181
6.46 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
619
22.1 IPS |
|
|
Text Classification (F32)
|
100% |
211
302.5 IPS |
|
|
Text Classification (F16)
|
100% |
211
302.6 IPS |
|
|
Text Classification (I8)
|
92% |
383
550.7 IPS |
|
|
Machine Translation (F32)
|
100% |
388
7.13 IPS |
|
|
Machine Translation (F16)
|
100% |
389
7.15 IPS |
|
|
Machine Translation (I8)
|
64% |
468
8.62 IPS |
