vivo V2352A
Geekbench ML Score
565
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 09 2025 02:54 PM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
293
54.8 IPS |
|
|
Image Classification (F16)
|
100% |
457
85.4 IPS |
|
|
Image Classification (I8)
|
99% |
427
79.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
374
6.25 IPS |
|
|
Image Segmentation (F16)
|
100% |
826
13.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
718
12.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
480
0.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
776
0.94 IPS |
|
|
Pose Estimation (I8)
|
100% |
779
0.94 IPS |
|
|
Object Detection (F32)
|
100% |
206
15.4 IPS |
|
|
Object Detection (F16)
|
100% |
296
22.1 IPS |
|
|
Object Detection (I8)
|
62% |
316
23.6 IPS |
|
|
Face Detection (F32)
|
100% |
839
9.98 IPS |
|
|
Face Detection (F16)
|
97% |
1456
17.3 IPS |
|
|
Face Detection (I8)
|
86% |
1409
16.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
601
4.66 IPS |
|
|
Depth Estimation (F16)
|
100% |
1032
8.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
999
7.75 IPS |
|
|
Style Transfer (F32)
|
100% |
1828
2.40 IPS |
|
|
Style Transfer (F16)
|
100% |
2875
3.78 IPS |
|
|
Style Transfer (I8)
|
98% |
2877
3.78 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
276
9.85 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
473
16.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
455
16.2 IPS |
|
|
Text Classification (F32)
|
100% |
152
218.9 IPS |
|
|
Text Classification (F16)
|
100% |
172
246.8 IPS |
|
|
Text Classification (I8)
|
92% |
499
717.5 IPS |
|
|
Machine Translation (F32)
|
100% |
401
7.38 IPS |
|
|
Machine Translation (F16)
|
100% |
312
5.74 IPS |
|
|
Machine Translation (I8)
|
64% |
340
6.25 IPS |
