vivo V2324A
Geekbench ML Score
1006
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 04:05 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2324A |
| Model ID | vivo V2324A |
| Motherboard | k6989v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 14.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
550
103.0 IPS |
|
|
Image Classification (F16)
|
100% |
685
128.1 IPS |
|
|
Image Classification (I8)
|
97% |
673
125.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1245
20.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1302
21.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1258
21.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
679
0.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
1017
1.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
1015
1.23 IPS |
|
|
Object Detection (F32)
|
100% |
435
32.5 IPS |
|
|
Object Detection (F16)
|
100% |
558
41.6 IPS |
|
|
Object Detection (I8)
|
62% |
586
43.8 IPS |
|
|
Face Detection (F32)
|
100% |
2457
29.2 IPS |
|
|
Face Detection (F16)
|
98% |
2731
32.5 IPS |
|
|
Face Detection (I8)
|
86% |
2401
28.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1376
10.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1716
13.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
1691
13.1 IPS |
|
|
Style Transfer (F32)
|
100% |
3825
5.03 IPS |
|
|
Style Transfer (F16)
|
100% |
4829
6.35 IPS |
|
|
Style Transfer (I8)
|
98% |
4807
6.32 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
763
27.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
954
34.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
934
33.3 IPS |
|
|
Text Classification (F32)
|
100% |
306
440.1 IPS |
|
|
Text Classification (F16)
|
100% |
306
439.9 IPS |
|
|
Text Classification (I8)
|
92% |
484
696.0 IPS |
|
|
Machine Translation (F32)
|
100% |
481
8.86 IPS |
|
|
Machine Translation (F16)
|
100% |
484
8.91 IPS |
|
|
Machine Translation (I8)
|
64% |
569
10.5 IPS |
