vivo V2352A
Geekbench ML Score
863
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 23 2024 01:39 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | 11.03 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
397
74.3 IPS |
|
|
Image Classification (F16)
|
100% |
410
76.7 IPS |
|
|
Image Classification (I8)
|
97% |
773
144.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
530
8.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
482
8.05 IPS |
|
|
Image Segmentation (I8)
|
98% |
573
9.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
989
1.20 IPS |
|
|
Pose Estimation (F16)
|
100% |
949
1.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
4202
5.09 IPS |
|
|
Object Detection (F32)
|
100% |
432
32.3 IPS |
|
|
Object Detection (F16)
|
100% |
437
32.6 IPS |
|
|
Object Detection (I8)
|
61% |
613
45.7 IPS |
|
|
Face Detection (F32)
|
100% |
966
11.5 IPS |
|
|
Face Detection (F16)
|
100% |
937
11.1 IPS |
|
|
Face Detection (I8)
|
86% |
1295
15.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
926
7.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
928
7.20 IPS |
|
|
Depth Estimation (I8)
|
95% |
1582
12.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1864
2.45 IPS |
|
|
Style Transfer (F16)
|
100% |
1841
2.42 IPS |
|
|
Style Transfer (I8)
|
98% |
4473
5.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
712
25.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
710
25.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1709
61.1 IPS |
|
|
Text Classification (F32)
|
100% |
628
902.5 IPS |
|
|
Text Classification (F16)
|
100% |
615
883.4 IPS |
|
|
Text Classification (I8)
|
92% |
434
624.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1075
19.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1061
19.5 IPS |
|
|
Machine Translation (I8)
|
64% |
358
6.58 IPS |
