vivo V2352GA
Geekbench ML Score
860
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 08 2025 11:24 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2352GA |
| Model ID | vivo V2352GA |
| 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 | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.01 GHz |
| Memory Information | |
|---|---|
| Size | 11.03 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
430
80.4 IPS |
|
|
Image Classification (F16)
|
100% |
426
79.7 IPS |
|
|
Image Classification (I8)
|
97% |
682
127.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
493
8.24 IPS |
|
|
Image Segmentation (F16)
|
100% |
471
7.87 IPS |
|
|
Image Segmentation (I8)
|
98% |
540
9.01 IPS |
|
|
Pose Estimation (F32)
|
100% |
991
1.20 IPS |
|
|
Pose Estimation (F16)
|
100% |
978
1.18 IPS |
|
|
Pose Estimation (I8)
|
100% |
4413
5.34 IPS |
|
|
Object Detection (F32)
|
100% |
430
32.1 IPS |
|
|
Object Detection (F16)
|
100% |
437
32.6 IPS |
|
|
Object Detection (I8)
|
61% |
738
55.1 IPS |
|
|
Face Detection (F32)
|
100% |
962
11.4 IPS |
|
|
Face Detection (F16)
|
100% |
966
11.5 IPS |
|
|
Face Detection (I8)
|
86% |
1288
15.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
950
7.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
985
7.64 IPS |
|
|
Depth Estimation (I8)
|
95% |
1626
12.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1794
2.36 IPS |
|
|
Style Transfer (F16)
|
100% |
1921
2.53 IPS |
|
|
Style Transfer (I8)
|
98% |
4487
5.90 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
666
23.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
699
25.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1661
59.3 IPS |
|
|
Text Classification (F32)
|
100% |
583
838.0 IPS |
|
|
Text Classification (F16)
|
100% |
563
809.1 IPS |
|
|
Text Classification (I8)
|
92% |
414
594.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1086
20.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1142
21.0 IPS |
|
|
Machine Translation (I8)
|
64% |
323
5.94 IPS |
