Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
2386
TensorFlow Lite GPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | September 05 2024 07:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Qualcomm msmnile_gvmq for arm64 |
| Model ID | Qualcomm msmnile_gvmq for arm64 |
| Motherboard | msmnile |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3403 revision 0 |
| Base Frequency | 2.59 GHz |
| Cluster 1 | 4 Cores @ 2.25 GHz |
| Cluster 2 | 4 Cores @ 2.59 GHz |
| Memory Information | |
|---|---|
| Size | 10.20 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
27% |
2188
234.4 IPS |
|
|
Image Classification (F16)
|
3% |
2839
304.2 IPS |
|
|
Image Classification (I8)
|
3% |
2828
303.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
5475
33.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
9213
56.9 IPS |
|
|
Image Segmentation (I8)
|
89% |
9419
58.2 IPS |
|
|
Pose Estimation (F32)
|
7% |
2712
11.0 IPS |
|
|
Pose Estimation (F16)
|
13% |
5184
21.0 IPS |
|
|
Pose Estimation (I8)
|
60% |
5182
21.0 IPS |
|
|
Object Detection (F32)
|
73% |
933
32.7 IPS |
|
|
Object Detection (F16)
|
76% |
1072
37.6 IPS |
|
|
Object Detection (I8)
|
41% |
1072
37.6 IPS |
|
|
Face Detection (F32)
|
33% |
3245
37.3 IPS |
|
|
Face Detection (F16)
|
27% |
5540
63.6 IPS |
|
|
Face Detection (I8)
|
34% |
5116
58.8 IPS |
|
|
Text Classification (F32)
|
54% |
635
251.3 IPS |
|
|
Text Classification (F16)
|
52% |
795
314.5 IPS |
|
|
Machine Translation (F32)
|
100% |
707
109.0 IPS |
|
|
Machine Translation (F16)
|
100% |
705
108.6 IPS |
