vivo V2329A
Geekbench ML Score
1017
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 09 2025 02:44 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2329A |
| Model ID | vivo V2329A |
| 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 | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.85 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
523
97.9 IPS |
|
|
Image Classification (F16)
|
100% |
492
92.0 IPS |
|
|
Image Classification (I8)
|
97% |
899
168.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
642
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
622
10.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
650
10.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1305
1.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
1310
1.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
5130
6.21 IPS |
|
|
Object Detection (F32)
|
100% |
537
40.1 IPS |
|
|
Object Detection (F16)
|
100% |
543
40.6 IPS |
|
|
Object Detection (I8)
|
61% |
659
49.2 IPS |
|
|
Face Detection (F32)
|
100% |
1087
12.9 IPS |
|
|
Face Detection (F16)
|
100% |
1079
12.8 IPS |
|
|
Face Detection (I8)
|
86% |
1904
22.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1150
8.92 IPS |
|
|
Depth Estimation (F16)
|
100% |
1185
9.19 IPS |
|
|
Depth Estimation (I8)
|
95% |
2024
15.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2332
3.07 IPS |
|
|
Style Transfer (F16)
|
100% |
2333
3.07 IPS |
|
|
Style Transfer (I8)
|
98% |
4677
6.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
874
31.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
812
29.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2103
75.1 IPS |
|
|
Text Classification (F32)
|
100% |
567
814.8 IPS |
|
|
Text Classification (F16)
|
100% |
544
781.9 IPS |
|
|
Text Classification (I8)
|
92% |
396
569.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1272
23.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1295
23.8 IPS |
|
|
Machine Translation (I8)
|
64% |
351
6.47 IPS |
