vivo V2329A
Geekbench ML Score
1041
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 29 2024 08:31 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2329A |
| Model ID | vivo V2329A |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.91 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
668
125.0 IPS |
|
|
Image Classification (F16)
|
100% |
690
129.1 IPS |
|
|
Image Classification (I8)
|
99% |
650
121.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
861
14.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1476
24.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1239
20.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
996
1.21 IPS |
|
|
Pose Estimation (F16)
|
100% |
2092
2.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
2076
2.51 IPS |
|
|
Object Detection (F32)
|
100% |
243
18.1 IPS |
|
|
Object Detection (F16)
|
100% |
395
29.5 IPS |
|
|
Object Detection (I8)
|
62% |
269
20.1 IPS |
|
|
Face Detection (F32)
|
100% |
2410
28.7 IPS |
|
|
Face Detection (F16)
|
97% |
3148
37.4 IPS |
|
|
Face Detection (I8)
|
86% |
2774
33.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1630
12.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
3112
24.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
3194
24.8 IPS |
|
|
Style Transfer (F32)
|
100% |
5584
7.35 IPS |
|
|
Style Transfer (F16)
|
100% |
9028
11.9 IPS |
|
|
Style Transfer (I8)
|
98% |
8947
11.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
435
15.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
999
35.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
960
34.3 IPS |
|
|
Text Classification (F32)
|
100% |
276
396.4 IPS |
|
|
Text Classification (F16)
|
100% |
196
281.5 IPS |
|
|
Text Classification (I8)
|
92% |
321
461.0 IPS |
|
|
Machine Translation (F32)
|
100% |
370
6.80 IPS |
|
|
Machine Translation (F16)
|
100% |
370
6.81 IPS |
|
|
Machine Translation (I8)
|
64% |
424
7.79 IPS |
