Nothing A065
Geekbench ML Score
723
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 12 2024 07:01 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% |
479
89.6 IPS |
|
|
Image Classification (F16)
|
100% |
389
72.8 IPS |
|
|
Image Classification (I8)
|
97% |
464
86.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
748
12.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
983
16.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
839
14.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
653
0.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
1206
1.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
1207
1.46 IPS |
|
|
Object Detection (F32)
|
100% |
262
19.5 IPS |
|
|
Object Detection (F16)
|
100% |
255
19.0 IPS |
|
|
Object Detection (I8)
|
62% |
240
17.9 IPS |
|
|
Face Detection (F32)
|
100% |
1450
17.2 IPS |
|
|
Face Detection (F16)
|
97% |
1447
17.2 IPS |
|
|
Face Detection (I8)
|
87% |
1328
15.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1059
8.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
2254
17.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2301
17.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2461
3.24 IPS |
|
|
Style Transfer (F16)
|
100% |
4809
6.33 IPS |
|
|
Style Transfer (I8)
|
98% |
4833
6.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
373
13.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
495
17.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
394
14.1 IPS |
|
|
Text Classification (F32)
|
100% |
210
301.5 IPS |
|
|
Text Classification (F16)
|
100% |
210
301.6 IPS |
|
|
Text Classification (I8)
|
92% |
381
548.1 IPS |
|
|
Machine Translation (F32)
|
100% |
386
7.11 IPS |
|
|
Machine Translation (F16)
|
100% |
388
7.14 IPS |
|
|
Machine Translation (I8)
|
64% |
465
8.56 IPS |
