Nothing A065
Geekbench ML Score
792
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 02 2024 03:22 PM |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
434
81.2 IPS |
|
|
Image Classification (F16)
|
100% |
394
73.7 IPS |
|
|
Image Classification (I8)
|
97% |
338
63.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
736
12.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
941
15.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
874
14.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
719
0.87 IPS |
|
|
Pose Estimation (F16)
|
100% |
1239
1.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
1252
1.52 IPS |
|
|
Object Detection (F32)
|
100% |
234
17.5 IPS |
|
|
Object Detection (F16)
|
100% |
262
19.6 IPS |
|
|
Object Detection (I8)
|
62% |
261
19.5 IPS |
|
|
Face Detection (F32)
|
100% |
1427
17.0 IPS |
|
|
Face Detection (F16)
|
97% |
1680
20.0 IPS |
|
|
Face Detection (I8)
|
87% |
1404
16.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1124
8.72 IPS |
|
|
Depth Estimation (F16)
|
100% |
2683
20.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2609
20.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2861
3.76 IPS |
|
|
Style Transfer (F16)
|
100% |
6436
8.47 IPS |
|
|
Style Transfer (I8)
|
98% |
6561
8.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
395
14.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
521
18.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
509
18.2 IPS |
|
|
Text Classification (F32)
|
100% |
269
386.6 IPS |
|
|
Text Classification (F16)
|
100% |
268
385.2 IPS |
|
|
Text Classification (I8)
|
92% |
486
698.7 IPS |
|
|
Machine Translation (F32)
|
100% |
466
8.58 IPS |
|
|
Machine Translation (F16)
|
100% |
468
8.60 IPS |
|
|
Machine Translation (I8)
|
64% |
591
10.9 IPS |
