vivo V2352A
Geekbench ML Score
482
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 09 2025 02:41 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
222
41.5 IPS |
|
|
Image Classification (F16)
|
100% |
219
41.1 IPS |
|
|
Image Classification (I8)
|
97% |
393
73.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
400
6.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
427
7.13 IPS |
|
|
Image Segmentation (I8)
|
98% |
547
9.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
744
0.90 IPS |
|
|
Pose Estimation (F16)
|
100% |
783
0.95 IPS |
|
|
Pose Estimation (I8)
|
100% |
3649
4.42 IPS |
|
|
Object Detection (F32)
|
100% |
210
15.7 IPS |
|
|
Object Detection (F16)
|
100% |
174
13.0 IPS |
|
|
Object Detection (I8)
|
61% |
585
43.7 IPS |
|
|
Face Detection (F32)
|
100% |
742
8.82 IPS |
|
|
Face Detection (F16)
|
100% |
727
8.65 IPS |
|
|
Face Detection (I8)
|
86% |
828
9.85 IPS |
|
|
Depth Estimation (F32)
|
100% |
513
3.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
511
3.96 IPS |
|
|
Depth Estimation (I8)
|
95% |
1185
9.19 IPS |
|
|
Style Transfer (F32)
|
100% |
1650
2.17 IPS |
|
|
Style Transfer (F16)
|
100% |
1541
2.03 IPS |
|
|
Style Transfer (I8)
|
98% |
3939
5.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
376
13.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
338
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
613
21.9 IPS |
|
|
Text Classification (F32)
|
100% |
130
186.9 IPS |
|
|
Text Classification (F16)
|
100% |
87
125.4 IPS |
|
|
Text Classification (I8)
|
92% |
116
167.3 IPS |
|
|
Machine Translation (F32)
|
100% |
259
4.77 IPS |
|
|
Machine Translation (F16)
|
100% |
451
8.31 IPS |
|
|
Machine Translation (I8)
|
64% |
241
4.43 IPS |
