HONOR BVL-N49
Geekbench ML Score
628
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 25 2024 12:03 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR BVL-N49 |
| Model ID | HONOR BVL-N49 |
| Motherboard | BVL |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 11.01 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
289
54.0 IPS |
|
|
Image Classification (F16)
|
100% |
281
52.6 IPS |
|
|
Image Classification (I8)
|
97% |
772
144.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
337
5.63 IPS |
|
|
Image Segmentation (F16)
|
100% |
336
5.61 IPS |
|
|
Image Segmentation (I8)
|
98% |
715
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
458
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
457
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1916
2.32 IPS |
|
|
Object Detection (F32)
|
100% |
306
22.9 IPS |
|
|
Object Detection (F16)
|
100% |
303
22.6 IPS |
|
|
Object Detection (I8)
|
61% |
812
60.6 IPS |
|
|
Face Detection (F32)
|
100% |
669
7.96 IPS |
|
|
Face Detection (F16)
|
100% |
662
7.88 IPS |
|
|
Face Detection (I8)
|
86% |
1621
19.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
578
4.48 IPS |
|
|
Depth Estimation (F16)
|
100% |
573
4.44 IPS |
|
|
Depth Estimation (I8)
|
95% |
1687
13.1 IPS |
|
|
Style Transfer (F32)
|
100% |
944
1.24 IPS |
|
|
Style Transfer (F16)
|
100% |
939
1.24 IPS |
|
|
Style Transfer (I8)
|
98% |
2352
3.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
344
12.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
344
12.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1222
43.6 IPS |
|
|
Text Classification (F32)
|
100% |
434
624.0 IPS |
|
|
Text Classification (F16)
|
100% |
434
623.6 IPS |
|
|
Text Classification (I8)
|
92% |
711
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
679
12.5 IPS |
|
|
Machine Translation (F16)
|
100% |
670
12.3 IPS |
|
|
Machine Translation (I8)
|
64% |
791
14.6 IPS |
