LG V50 ThinQ 5G
Geekbench AI Score
682
Single Precision Score
676
Half Precision Score
1130
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | cnliyx |
| Upload Date | December 20 2024 06:20 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 855 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | LG V50 ThinQ 5G |
| Model ID | LGE LM-V500N |
| Motherboard | msmnile |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 5.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
312
58.0 IPS |
|
|
Image Classification (HP)
|
100% |
325
60.4 IPS |
|
|
Image Classification (Q)
|
100% |
848
157.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
416
6.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
415
6.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
1002
16.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1492
1.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
1386
1.62 IPS |
|
|
Pose Estimation (Q)
|
84% |
1926
2.28 IPS |
|
|
Object Detection (SP)
|
100% |
306
24.3 IPS |
|
|
Object Detection (HP)
|
100% |
333
26.4 IPS |
|
|
Object Detection (Q)
|
83% |
892
72.0 IPS |
|
|
Face Detection (SP)
|
100% |
1067
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
1045
12.4 IPS |
|
|
Face Detection (Q)
|
95% |
2023
24.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1232
9.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
1280
9.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
2079
19.0 IPS |
|
|
Style Transfer (SP)
|
89% |
2535
3.29 IPS |
|
|
Style Transfer (HP)
|
89% |
2358
3.06 IPS |
|
|
Style Transfer (Q)
|
98% |
4147
5.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
709
26.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
691
25.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1026
38.0 IPS |
|
|
Text Classification (SP)
|
100% |
288
384.2 IPS |
|
|
Text Classification (HP)
|
100% |
289
385.3 IPS |
|
|
Text Classification (Q)
|
88% |
460
620.5 IPS |
|
|
Machine Translation (SP)
|
100% |
540
9.31 IPS |
|
|
Machine Translation (HP)
|
100% |
510
8.79 IPS |
|
|
Machine Translation (Q)
|
50% |
284
10.1 IPS |
