Huawei Honor V30 Pro
Geekbench ML Score
584
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 19 2024 12:03 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Huawei Honor V30 Pro |
| Model ID | HUAWEI OXF-AN10 |
| Motherboard | OXF |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 72 architecture 8 variant 3 part 3392 revision 1 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.36 GHz |
| Cluster 3 | 2 Cores @ 2.86 GHz |
| Memory Information | |
|---|---|
| Size | 7.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
272
50.9 IPS |
|
|
Image Classification (F16)
|
100% |
278
52.1 IPS |
|
|
Image Classification (I8)
|
97% |
541
101.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
397
6.62 IPS |
|
|
Image Segmentation (F16)
|
100% |
391
6.52 IPS |
|
|
Image Segmentation (I8)
|
98% |
486
8.11 IPS |
|
|
Pose Estimation (F32)
|
100% |
631
0.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
626
0.76 IPS |
|
|
Pose Estimation (I8)
|
100% |
2772
3.36 IPS |
|
|
Object Detection (F32)
|
100% |
313
23.4 IPS |
|
|
Object Detection (F16)
|
100% |
313
23.3 IPS |
|
|
Object Detection (I8)
|
61% |
750
56.0 IPS |
|
|
Face Detection (F32)
|
100% |
645
7.66 IPS |
|
|
Face Detection (F16)
|
100% |
657
7.82 IPS |
|
|
Face Detection (I8)
|
86% |
1237
14.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
634
4.92 IPS |
|
|
Depth Estimation (F16)
|
100% |
615
4.77 IPS |
|
|
Depth Estimation (I8)
|
95% |
1313
10.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1011
1.33 IPS |
|
|
Style Transfer (F16)
|
100% |
991
1.30 IPS |
|
|
Style Transfer (I8)
|
98% |
2709
3.56 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
352
12.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
343
12.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1213
43.3 IPS |
|
|
Text Classification (F32)
|
100% |
326
469.1 IPS |
|
|
Text Classification (F16)
|
100% |
327
469.6 IPS |
|
|
Text Classification (I8)
|
92% |
272
390.8 IPS |
|
|
Machine Translation (F32)
|
100% |
642
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
643
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
311
5.72 IPS |
