vivo V2218A
Geekbench ML Score
1581
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 20 2024 06:14 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | vivo V2218A |
| Model ID | vivo V2218A |
| Motherboard | V2218A |
| Governor | performance |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores @ 3.20 GHz |
| Memory Information | |
|---|---|
| Size | 5.81 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
742
138.9 IPS |
|
|
Image Classification (F16)
|
100% |
2152
402.8 IPS |
|
|
Image Classification (I8)
|
99% |
1848
345.8 IPS |
|
|
Image Segmentation (F32)
|
98% |
793
13.3 IPS |
|
|
Image Segmentation (F16)
|
98% |
1707
28.5 IPS |
|
|
Image Segmentation (I8)
|
96% |
1143
19.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
4999
6.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
9655
11.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
9450
11.4 IPS |
|
|
Object Detection (F32)
|
91% |
710
53.0 IPS |
|
|
Object Detection (F16)
|
86% |
1335
99.6 IPS |
|
|
Object Detection (I8)
|
37% |
1305
97.5 IPS |
|
|
Face Detection (F32)
|
100% |
1288
15.3 IPS |
|
|
Face Detection (F16)
|
97% |
6075
72.2 IPS |
|
|
Face Detection (I8)
|
87% |
4991
59.3 IPS |
|
|
Depth Estimation (F32)
|
90% |
2954
22.9 IPS |
|
|
Depth Estimation (F16)
|
89% |
6706
52.0 IPS |
|
|
Depth Estimation (I8)
|
90% |
6830
53.0 IPS |
|
|
Style Transfer (F32)
|
100% |
9952
13.1 IPS |
|
|
Style Transfer (F16)
|
100% |
24926
32.8 IPS |
|
|
Style Transfer (I8)
|
98% |
23034
30.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1473
52.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3405
121.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1791
64.0 IPS |
|
|
Text Classification (F32)
|
100% |
106
152.6 IPS |
|
|
Text Classification (F16)
|
100% |
107
153.1 IPS |
|
|
Text Classification (I8)
|
92% |
37
53.5 IPS |
|
|
Machine Translation (F32)
|
100% |
215
3.96 IPS |
|
|
Machine Translation (F16)
|
100% |
218
4.02 IPS |
|
|
Machine Translation (I8)
|
64% |
68
1.26 IPS |
