vivo V2352A
Geekbench ML Score
914
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 09 2025 07:32 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2352A |
| Model ID | vivo V2352A |
| 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% |
399
74.7 IPS |
|
|
Image Classification (F16)
|
100% |
420
78.6 IPS |
|
|
Image Classification (I8)
|
97% |
892
166.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
615
10.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
596
9.95 IPS |
|
|
Image Segmentation (I8)
|
98% |
584
9.76 IPS |
|
|
Pose Estimation (F32)
|
100% |
945
1.14 IPS |
|
|
Pose Estimation (F16)
|
100% |
948
1.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
4782
5.79 IPS |
|
|
Object Detection (F32)
|
100% |
476
35.5 IPS |
|
|
Object Detection (F16)
|
100% |
455
34.0 IPS |
|
|
Object Detection (I8)
|
61% |
1005
75.1 IPS |
|
|
Face Detection (F32)
|
100% |
1048
12.5 IPS |
|
|
Face Detection (F16)
|
100% |
1055
12.5 IPS |
|
|
Face Detection (I8)
|
86% |
1712
20.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
989
7.67 IPS |
|
|
Depth Estimation (F16)
|
100% |
941
7.29 IPS |
|
|
Depth Estimation (I8)
|
95% |
1907
14.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1915
2.52 IPS |
|
|
Style Transfer (F16)
|
100% |
1963
2.58 IPS |
|
|
Style Transfer (I8)
|
98% |
4865
6.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
709
25.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
702
25.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1868
66.7 IPS |
|
|
Text Classification (F32)
|
100% |
571
820.0 IPS |
|
|
Text Classification (F16)
|
100% |
486
698.9 IPS |
|
|
Text Classification (I8)
|
92% |
339
487.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1020
18.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1017
18.7 IPS |
|
|
Machine Translation (I8)
|
64% |
413
7.61 IPS |
