vivo V2304A
Geekbench ML Score
937
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2024 06:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2304A |
| Model ID | vivo V2304A |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 14.88 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
469
87.7 IPS |
|
|
Image Classification (F16)
|
100% |
467
87.4 IPS |
|
|
Image Classification (I8)
|
97% |
815
152.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
691
11.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
665
11.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
740
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1069
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
1101
1.33 IPS |
|
|
Pose Estimation (I8)
|
100% |
4803
5.82 IPS |
|
|
Object Detection (F32)
|
100% |
526
39.3 IPS |
|
|
Object Detection (F16)
|
100% |
527
39.3 IPS |
|
|
Object Detection (I8)
|
61% |
998
74.5 IPS |
|
|
Face Detection (F32)
|
100% |
976
11.6 IPS |
|
|
Face Detection (F16)
|
100% |
901
10.7 IPS |
|
|
Face Detection (I8)
|
86% |
1383
16.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1041
8.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
1049
8.13 IPS |
|
|
Depth Estimation (I8)
|
95% |
1801
14.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1989
2.62 IPS |
|
|
Style Transfer (F16)
|
100% |
2043
2.69 IPS |
|
|
Style Transfer (I8)
|
98% |
3604
4.74 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
718
25.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
743
26.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1977
70.6 IPS |
|
|
Text Classification (F32)
|
100% |
553
795.0 IPS |
|
|
Text Classification (F16)
|
100% |
524
753.6 IPS |
|
|
Text Classification (I8)
|
92% |
355
510.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1014
18.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1034
19.0 IPS |
|
|
Machine Translation (I8)
|
64% |
376
6.92 IPS |
