Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
583
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | September 05 2024 07:13 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 | CPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
550
58.9 IPS |
|
|
Image Classification (F16)
|
100% |
506
54.2 IPS |
|
|
Image Classification (I8)
|
81% |
201
21.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
866
5.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
845
5.22 IPS |
|
|
Image Segmentation (I8)
|
89% |
1221
7.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
485
1.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
491
1.99 IPS |
|
|
Pose Estimation (I8)
|
80% |
414
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
588
20.6 IPS |
|
|
Object Detection (F16)
|
100% |
593
20.8 IPS |
|
|
Object Detection (I8)
|
52% |
353
12.4 IPS |
|
|
Face Detection (F32)
|
100% |
837
9.62 IPS |
|
|
Face Detection (F16)
|
100% |
836
9.61 IPS |
|
|
Face Detection (I8)
|
75% |
552
6.34 IPS |
|
|
Text Classification (F32)
|
100% |
611
241.7 IPS |
|
|
Text Classification (F16)
|
100% |
498
197.1 IPS |
|
|
Machine Translation (F32)
|
100% |
713
109.9 IPS |
|
|
Machine Translation (F16)
|
100% |
706
108.8 IPS |
