Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
532
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | September 19 2024 09:04 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 | NNAPI |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
452
48.4 IPS |
|
|
Image Classification (F16)
|
100% |
510
54.6 IPS |
|
|
Image Classification (I8)
|
81% |
358
38.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
745
4.60 IPS |
|
|
Image Segmentation (F16)
|
100% |
735
4.54 IPS |
|
|
Image Segmentation (I8)
|
89% |
656
4.05 IPS |
|
|
Pose Estimation (F32)
|
100% |
407
1.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
406
1.64 IPS |
|
|
Pose Estimation (I8)
|
80% |
113
0.46 IPS |
|
|
Object Detection (F32)
|
100% |
529
18.6 IPS |
|
|
Object Detection (F16)
|
100% |
529
18.6 IPS |
|
|
Object Detection (I8)
|
52% |
398
14.0 IPS |
|
|
Face Detection (F32)
|
100% |
694
7.97 IPS |
|
|
Face Detection (F16)
|
100% |
708
8.13 IPS |
|
|
Face Detection (I8)
|
75% |
487
5.59 IPS |
|
|
Text Classification (F32)
|
100% |
937
370.4 IPS |
|
|
Text Classification (F16)
|
100% |
933
369.2 IPS |
|
|
Machine Translation (F32)
|
100% |
708
109.1 IPS |
|
|
Machine Translation (F16)
|
100% |
703
108.3 IPS |
