Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
590
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | December 23 2024 01:34 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 | CPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
517
55.4 IPS |
|
|
Image Classification (F16)
|
100% |
544
58.3 IPS |
|
|
Image Classification (I8)
|
81% |
304
32.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
842
5.20 IPS |
|
|
Image Segmentation (F16)
|
100% |
825
5.10 IPS |
|
|
Image Segmentation (I8)
|
89% |
1217
7.52 IPS |
|
|
Pose Estimation (F32)
|
100% |
475
1.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
471
1.90 IPS |
|
|
Pose Estimation (I8)
|
80% |
405
1.64 IPS |
|
|
Object Detection (F32)
|
100% |
588
20.6 IPS |
|
|
Object Detection (F16)
|
100% |
588
20.6 IPS |
|
|
Object Detection (I8)
|
52% |
385
13.5 IPS |
|
|
Face Detection (F32)
|
100% |
844
9.70 IPS |
|
|
Face Detection (F16)
|
100% |
851
9.78 IPS |
|
|
Face Detection (I8)
|
75% |
599
6.88 IPS |
|
|
Text Classification (F32)
|
100% |
484
191.5 IPS |
|
|
Text Classification (F16)
|
100% |
503
198.9 IPS |
|
|
Machine Translation (F32)
|
100% |
701
108.0 IPS |
|
|
Machine Translation (F16)
|
100% |
694
107.0 IPS |
