Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
520
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | January 07 2025 09:08 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 | NNAPI |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
480
51.4 IPS |
|
|
Image Classification (F16)
|
100% |
484
51.9 IPS |
|
|
Image Classification (I8)
|
81% |
352
37.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
732
4.52 IPS |
|
|
Image Segmentation (F16)
|
100% |
718
4.43 IPS |
|
|
Image Segmentation (I8)
|
89% |
653
4.03 IPS |
|
|
Pose Estimation (F32)
|
100% |
384
1.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
386
1.56 IPS |
|
|
Pose Estimation (I8)
|
80% |
112
0.45 IPS |
|
|
Object Detection (F32)
|
100% |
507
17.8 IPS |
|
|
Object Detection (F16)
|
100% |
500
17.6 IPS |
|
|
Object Detection (I8)
|
52% |
397
13.9 IPS |
|
|
Face Detection (F32)
|
100% |
612
7.03 IPS |
|
|
Face Detection (F16)
|
100% |
694
7.97 IPS |
|
|
Face Detection (I8)
|
75% |
484
5.56 IPS |
|
|
Text Classification (F32)
|
100% |
930
367.8 IPS |
|
|
Text Classification (F16)
|
100% |
932
368.5 IPS |
|
|
Machine Translation (F32)
|
100% |
696
107.2 IPS |
|
|
Machine Translation (F16)
|
100% |
700
107.9 IPS |
