LGE LM-V600
Geekbench AI Score
376
Single Precision Score
653
Half Precision Score
660
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 23 2025 08:54 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | LGE LM-V600 |
| Model ID | LGE LM-V600 |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
252
46.9 IPS |
|
|
Image Classification (HP)
|
100% |
369
68.6 IPS |
|
|
Image Classification (Q)
|
97% |
370
69.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
365
5.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
746
12.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
728
11.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
493
0.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
996
1.16 IPS |
|
|
Pose Estimation (Q)
|
95% |
989
1.16 IPS |
|
|
Object Detection (SP)
|
100% |
224
17.8 IPS |
|
|
Object Detection (HP)
|
100% |
332
26.4 IPS |
|
|
Object Detection (Q)
|
89% |
347
27.8 IPS |
|
|
Face Detection (SP)
|
100% |
666
7.92 IPS |
|
|
Face Detection (HP)
|
100% |
1365
16.2 IPS |
|
|
Face Detection (Q)
|
97% |
1394
16.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
588
4.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
1156
8.93 IPS |
|
|
Depth Estimation (Q)
|
62% |
939
8.89 IPS |
|
|
Style Transfer (SP)
|
100% |
1125
1.45 IPS |
|
|
Style Transfer (HP)
|
100% |
2936
3.77 IPS |
|
|
Style Transfer (Q)
|
98% |
2925
3.77 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
281
10.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
634
23.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
624
23.1 IPS |
|
|
Text Classification (SP)
|
100% |
144
192.0 IPS |
|
|
Text Classification (HP)
|
100% |
165
220.4 IPS |
|
|
Text Classification (Q)
|
91% |
308
414.3 IPS |
|
|
Machine Translation (SP)
|
100% |
318
5.49 IPS |
|
|
Machine Translation (HP)
|
100% |
320
5.50 IPS |
|
|
Machine Translation (Q)
|
57% |
232
5.66 IPS |
