vivo V2022
Geekbench AI Score
28
Single Precision Score
89
Half Precision Score
84
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | October 05 2024 01:12 AM |
| Views | 16 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | vivo V2022 |
| Model ID | vivo V2022 |
| Motherboard | trinket |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
28
5.19 IPS |
|
|
Image Classification (HP)
|
100% |
57
10.6 IPS |
|
|
Image Classification (Q)
|
97% |
58
10.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
27
0.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
83
1.34 IPS |
|
|
Image Segmentation (Q)
|
98% |
85
1.38 IPS |
|
|
Pose Estimation (SP)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
98
0.11 IPS |
|
|
Pose Estimation (Q)
|
95% |
98
0.11 IPS |
|
|
Object Detection (SP)
|
100% |
28
2.20 IPS |
|
|
Object Detection (HP)
|
100% |
47
3.69 IPS |
|
|
Object Detection (Q)
|
89% |
46
3.71 IPS |
|
|
Face Detection (SP)
|
100% |
70
0.83 IPS |
|
|
Face Detection (HP)
|
100% |
172
2.04 IPS |
|
|
Face Detection (Q)
|
97% |
177
2.12 IPS |
|
|
Depth Estimation (SP)
|
100% |
65
0.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
136
1.05 IPS |
|
|
Depth Estimation (Q)
|
62% |
111
1.05 IPS |
|
|
Style Transfer (SP)
|
0
|
||
|
Style Transfer (HP)
|
100% |
257
0.33 IPS |
|
|
Style Transfer (Q)
|
98% |
255
0.33 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
32
1.18 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
68
2.52 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
68
2.51 IPS |
|
|
Text Classification (SP)
|
100% |
28
36.8 IPS |
|
|
Text Classification (HP)
|
100% |
48
64.4 IPS |
|
|
Text Classification (Q)
|
91% |
38
51.5 IPS |
|
|
Machine Translation (SP)
|
100% |
81
1.39 IPS |
|
|
Machine Translation (HP)
|
100% |
81
1.39 IPS |
|
|
Machine Translation (Q)
|
57% |
62
1.53 IPS |
