Nothing A065
Geekbench ML Score
785
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 02:13 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
483
90.3 IPS |
|
|
Image Classification (F16)
|
100% |
562
105.2 IPS |
|
|
Image Classification (I8)
|
97% |
530
99.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
731
12.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
926
15.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
877
14.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
683
0.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
1213
1.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
1269
1.54 IPS |
|
|
Object Detection (F32)
|
100% |
226
16.9 IPS |
|
|
Object Detection (F16)
|
100% |
247
18.5 IPS |
|
|
Object Detection (I8)
|
62% |
593
44.3 IPS |
|
|
Face Detection (F32)
|
100% |
1441
17.1 IPS |
|
|
Face Detection (F16)
|
97% |
1477
17.6 IPS |
|
|
Face Detection (I8)
|
87% |
2359
28.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1052
8.16 IPS |
|
|
Depth Estimation (F16)
|
100% |
2415
18.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
2371
18.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2570
3.38 IPS |
|
|
Style Transfer (F16)
|
100% |
5698
7.50 IPS |
|
|
Style Transfer (I8)
|
98% |
4831
6.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
374
13.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
493
17.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
513
18.3 IPS |
|
|
Text Classification (F32)
|
100% |
210
301.4 IPS |
|
|
Text Classification (F16)
|
100% |
210
301.4 IPS |
|
|
Text Classification (I8)
|
92% |
382
549.0 IPS |
|
|
Machine Translation (F32)
|
100% |
388
7.15 IPS |
|
|
Machine Translation (F16)
|
100% |
390
7.17 IPS |
|
|
Machine Translation (I8)
|
64% |
469
8.63 IPS |
