vivo V2324A
Geekbench ML Score
945
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 04:01 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
500
93.5 IPS |
|
|
Image Classification (F16)
|
100% |
564
105.5 IPS |
|
|
Image Classification (I8)
|
97% |
770
144.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
853
14.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
839
14.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
806
13.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1163
1.41 IPS |
|
|
Pose Estimation (F16)
|
100% |
1126
1.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
4534
5.49 IPS |
|
|
Object Detection (F32)
|
100% |
537
40.1 IPS |
|
|
Object Detection (F16)
|
100% |
488
36.5 IPS |
|
|
Object Detection (I8)
|
61% |
710
53.0 IPS |
|
|
Face Detection (F32)
|
100% |
983
11.7 IPS |
|
|
Face Detection (F16)
|
100% |
1228
14.6 IPS |
|
|
Face Detection (I8)
|
86% |
1506
17.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1085
8.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
1013
7.86 IPS |
|
|
Depth Estimation (I8)
|
95% |
1630
12.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1816
2.39 IPS |
|
|
Style Transfer (F16)
|
100% |
1872
2.46 IPS |
|
|
Style Transfer (I8)
|
98% |
3896
5.12 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
659
23.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
605
21.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1024
36.6 IPS |
|
|
Text Classification (F32)
|
100% |
560
804.5 IPS |
|
|
Text Classification (F16)
|
100% |
609
875.5 IPS |
|
|
Text Classification (I8)
|
92% |
521
748.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1027
18.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1072
19.7 IPS |
|
|
Machine Translation (I8)
|
64% |
391
7.20 IPS |
