Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
2389
TensorFlow Lite GPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | September 05 2024 02:29 AM |
| Views | 3 |
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)
|
21% |
2126
227.8 IPS |
|
|
Image Classification (F16)
|
3% |
3032
324.9 IPS |
|
|
Image Classification (I8)
|
6% |
2701
289.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
5469
33.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
9192
56.8 IPS |
|
|
Image Segmentation (I8)
|
89% |
9384
58.0 IPS |
|
|
Pose Estimation (F32)
|
33% |
2714
11.0 IPS |
|
|
Pose Estimation (F16)
|
67% |
5205
21.1 IPS |
|
|
Pose Estimation (I8)
|
0% |
5201
21.0 IPS |
|
|
Object Detection (F32)
|
86% |
927
32.5 IPS |
|
|
Object Detection (F16)
|
71% |
1062
37.3 IPS |
|
|
Object Detection (I8)
|
36% |
1067
37.4 IPS |
|
|
Face Detection (F32)
|
42% |
3271
37.6 IPS |
|
|
Face Detection (F16)
|
68% |
5541
63.7 IPS |
|
|
Face Detection (I8)
|
35% |
5135
59.0 IPS |
|
|
Text Classification (F32)
|
56% |
711
281.4 IPS |
|
|
Text Classification (F16)
|
46% |
752
297.5 IPS |
|
|
Machine Translation (F32)
|
100% |
701
108.1 IPS |
|
|
Machine Translation (F16)
|
100% |
697
107.4 IPS |
