Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
530
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | January 07 2025 07:25 AM |
| Views | 5 |
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% |
466
49.9 IPS |
|
|
Image Classification (F16)
|
100% |
489
52.3 IPS |
|
|
Image Classification (I8)
|
81% |
187
20.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
762
4.71 IPS |
|
|
Image Segmentation (F16)
|
100% |
768
4.74 IPS |
|
|
Image Segmentation (I8)
|
89% |
1098
6.78 IPS |
|
|
Pose Estimation (F32)
|
100% |
411
1.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
413
1.67 IPS |
|
|
Pose Estimation (I8)
|
80% |
357
1.44 IPS |
|
|
Object Detection (F32)
|
100% |
551
19.3 IPS |
|
|
Object Detection (F16)
|
100% |
534
18.8 IPS |
|
|
Object Detection (I8)
|
52% |
339
11.9 IPS |
|
|
Face Detection (F32)
|
100% |
757
8.70 IPS |
|
|
Face Detection (F16)
|
100% |
788
9.05 IPS |
|
|
Face Detection (I8)
|
75% |
588
6.75 IPS |
|
|
Text Classification (F32)
|
100% |
469
185.6 IPS |
|
|
Text Classification (F16)
|
100% |
474
187.5 IPS |
|
|
Machine Translation (F32)
|
100% |
668
103.0 IPS |
|
|
Machine Translation (F16)
|
100% |
674
103.8 IPS |
