vivo PA2473
Geekbench ML Score
1156
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 12:10 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo PA2473 |
| Model ID | vivo PA2473 |
| Motherboard | tb8796p1_64_sp |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 15.20 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
694
129.8 IPS |
|
|
Image Classification (F16)
|
100% |
747
139.7 IPS |
|
|
Image Classification (I8)
|
97% |
684
128.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1456
24.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1623
27.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1686
28.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
764
0.93 IPS |
|
|
Pose Estimation (F16)
|
100% |
1153
1.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1147
1.39 IPS |
|
|
Object Detection (F32)
|
100% |
485
36.2 IPS |
|
|
Object Detection (F16)
|
100% |
629
47.0 IPS |
|
|
Object Detection (I8)
|
62% |
520
38.8 IPS |
|
|
Face Detection (F32)
|
100% |
2443
29.0 IPS |
|
|
Face Detection (F16)
|
98% |
3373
40.1 IPS |
|
|
Face Detection (I8)
|
86% |
2762
32.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1687
13.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2294
17.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2200
17.1 IPS |
|
|
Style Transfer (F32)
|
100% |
4169
5.48 IPS |
|
|
Style Transfer (F16)
|
100% |
5441
7.16 IPS |
|
|
Style Transfer (I8)
|
98% |
5236
6.89 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
781
27.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1013
36.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1061
37.9 IPS |
|
|
Text Classification (F32)
|
100% |
384
551.5 IPS |
|
|
Text Classification (F16)
|
100% |
383
550.1 IPS |
|
|
Text Classification (I8)
|
92% |
615
883.7 IPS |
|
|
Machine Translation (F32)
|
100% |
549
10.1 IPS |
|
|
Machine Translation (F16)
|
100% |
552
10.2 IPS |
|
|
Machine Translation (I8)
|
64% |
660
12.1 IPS |
