vivo V2352A
Geekbench ML Score
302
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 09 2025 02:50 PM |
| Views | 3 |
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 | 14.94 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
200
37.5 IPS |
|
|
Image Classification (F16)
|
100% |
160
30.0 IPS |
|
|
Image Classification (I8)
|
97% |
306
57.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
152
2.54 IPS |
|
|
Image Segmentation (F16)
|
100% |
152
2.54 IPS |
|
|
Image Segmentation (I8)
|
98% |
315
5.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
274
0.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
240
0.29 IPS |
|
|
Pose Estimation (I8)
|
100% |
777
0.94 IPS |
|
|
Object Detection (F32)
|
100% |
120
8.99 IPS |
|
|
Object Detection (F16)
|
100% |
120
8.99 IPS |
|
|
Object Detection (I8)
|
61% |
334
24.9 IPS |
|
|
Face Detection (F32)
|
100% |
331
3.94 IPS |
|
|
Face Detection (F16)
|
100% |
354
4.21 IPS |
|
|
Face Detection (I8)
|
86% |
847
10.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
289
2.24 IPS |
|
|
Depth Estimation (F16)
|
100% |
378
2.93 IPS |
|
|
Depth Estimation (I8)
|
95% |
761
5.90 IPS |
|
|
Style Transfer (F32)
|
100% |
498
0.66 IPS |
|
|
Style Transfer (F16)
|
100% |
499
0.66 IPS |
|
|
Style Transfer (I8)
|
98% |
1420
1.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
138
4.94 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
157
5.61 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
475
17.0 IPS |
|
|
Text Classification (F32)
|
100% |
152
217.7 IPS |
|
|
Text Classification (F16)
|
100% |
151
217.4 IPS |
|
|
Text Classification (I8)
|
92% |
500
718.8 IPS |
|
|
Machine Translation (F32)
|
100% |
429
7.90 IPS |
|
|
Machine Translation (F16)
|
100% |
295
5.42 IPS |
|
|
Machine Translation (I8)
|
64% |
338
6.23 IPS |
