Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
2349
TensorFlow Lite GPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | December 23 2024 01:36 AM |
| Views | 4 |
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)
|
100% |
2383
255.3 IPS |
|
|
Image Classification (F16)
|
100% |
2943
315.3 IPS |
|
|
Image Classification (I8)
|
80% |
2795
299.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
5154
31.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
8915
55.1 IPS |
|
|
Image Segmentation (I8)
|
89% |
9144
56.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
2641
10.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
5072
20.5 IPS |
|
|
Pose Estimation (I8)
|
80% |
5003
20.2 IPS |
|
|
Object Detection (F32)
|
100% |
908
31.9 IPS |
|
|
Object Detection (F16)
|
99% |
1052
36.9 IPS |
|
|
Object Detection (I8)
|
53% |
1053
37.0 IPS |
|
|
Face Detection (F32)
|
100% |
3191
36.7 IPS |
|
|
Face Detection (F16)
|
97% |
5404
62.1 IPS |
|
|
Face Detection (I8)
|
75% |
5066
58.2 IPS |
|
|
Text Classification (F32)
|
100% |
667
263.7 IPS |
|
|
Text Classification (F16)
|
98% |
719
284.4 IPS |
|
|
Machine Translation (F32)
|
100% |
687
105.9 IPS |
|
|
Machine Translation (F16)
|
100% |
700
107.9 IPS |
