Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
2334
TensorFlow Lite GPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | December 23 2024 07:42 AM |
| Views | 3 |
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 | GPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2065
221.3 IPS |
|
|
Image Classification (F16)
|
100% |
2899
310.6 IPS |
|
|
Image Classification (I8)
|
80% |
2784
298.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
5305
32.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
8961
55.4 IPS |
|
|
Image Segmentation (I8)
|
89% |
9185
56.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
2648
10.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
5020
20.3 IPS |
|
|
Pose Estimation (I8)
|
80% |
5015
20.3 IPS |
|
|
Object Detection (F32)
|
100% |
904
31.7 IPS |
|
|
Object Detection (F16)
|
99% |
1027
36.1 IPS |
|
|
Object Detection (I8)
|
53% |
1060
37.2 IPS |
|
|
Face Detection (F32)
|
100% |
3300
37.9 IPS |
|
|
Face Detection (F16)
|
97% |
5386
61.9 IPS |
|
|
Face Detection (I8)
|
75% |
5078
58.3 IPS |
|
|
Text Classification (F32)
|
100% |
637
251.9 IPS |
|
|
Text Classification (F16)
|
98% |
772
305.4 IPS |
|
|
Machine Translation (F32)
|
100% |
695
107.1 IPS |
|
|
Machine Translation (F16)
|
100% |
673
103.8 IPS |
