Qualcomm msmnile_gvmq for arm64
Geekbench ML Score
623
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | September 19 2024 08:59 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% |
554
59.3 IPS |
|
|
Image Classification (F16)
|
100% |
550
58.9 IPS |
|
|
Image Classification (I8)
|
81% |
302
32.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
892
5.51 IPS |
|
|
Image Segmentation (F16)
|
100% |
893
5.52 IPS |
|
|
Image Segmentation (I8)
|
89% |
1293
7.99 IPS |
|
|
Pose Estimation (F32)
|
100% |
551
2.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
546
2.21 IPS |
|
|
Pose Estimation (I8)
|
80% |
444
1.80 IPS |
|
|
Object Detection (F32)
|
100% |
592
20.8 IPS |
|
|
Object Detection (F16)
|
100% |
576
20.2 IPS |
|
|
Object Detection (I8)
|
52% |
320
11.2 IPS |
|
|
Face Detection (F32)
|
100% |
839
9.63 IPS |
|
|
Face Detection (F16)
|
100% |
838
9.62 IPS |
|
|
Face Detection (I8)
|
75% |
1058
12.2 IPS |
|
|
Text Classification (F32)
|
100% |
502
198.4 IPS |
|
|
Text Classification (F16)
|
100% |
492
194.6 IPS |
|
|
Machine Translation (F32)
|
100% |
703
108.4 IPS |
|
|
Machine Translation (F16)
|
100% |
700
107.9 IPS |
