vivo V2329A
Geekbench ML Score
1074
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 09 2024 04:30 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | 14.91 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
499
93.5 IPS |
|
|
Image Classification (F16)
|
100% |
521
97.5 IPS |
|
|
Image Classification (I8)
|
97% |
990
185.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
751
12.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
694
11.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
713
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1257
1.52 IPS |
|
|
Pose Estimation (F16)
|
100% |
1171
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
5646
6.84 IPS |
|
|
Object Detection (F32)
|
100% |
520
38.8 IPS |
|
|
Object Detection (F16)
|
100% |
525
39.2 IPS |
|
|
Object Detection (I8)
|
61% |
901
67.3 IPS |
|
|
Face Detection (F32)
|
100% |
1229
14.6 IPS |
|
|
Face Detection (F16)
|
100% |
1237
14.7 IPS |
|
|
Face Detection (I8)
|
86% |
1778
21.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1287
9.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
1195
9.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
2079
16.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2337
3.07 IPS |
|
|
Style Transfer (F16)
|
100% |
2333
3.07 IPS |
|
|
Style Transfer (I8)
|
98% |
5318
6.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
969
34.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
881
31.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2197
78.5 IPS |
|
|
Text Classification (F32)
|
100% |
653
938.8 IPS |
|
|
Text Classification (F16)
|
100% |
621
893.0 IPS |
|
|
Text Classification (I8)
|
92% |
368
529.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1309
24.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1177
21.7 IPS |
|
|
Machine Translation (I8)
|
64% |
407
7.48 IPS |
