HONOR BVL-N49
Geekbench ML Score
919
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 19 2024 06:58 AM |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
476
89.1 IPS |
|
|
Image Classification (F16)
|
100% |
439
82.2 IPS |
|
|
Image Classification (I8)
|
97% |
722
135.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
588
9.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
586
9.78 IPS |
|
|
Image Segmentation (I8)
|
98% |
581
9.70 IPS |
|
|
Pose Estimation (F32)
|
100% |
1091
1.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
1123
1.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
4206
5.09 IPS |
|
|
Object Detection (F32)
|
100% |
464
34.7 IPS |
|
|
Object Detection (F16)
|
100% |
461
34.4 IPS |
|
|
Object Detection (I8)
|
61% |
860
64.2 IPS |
|
|
Face Detection (F32)
|
100% |
1124
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
1133
13.5 IPS |
|
|
Face Detection (I8)
|
86% |
1799
21.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1120
8.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
1136
8.81 IPS |
|
|
Depth Estimation (I8)
|
95% |
1822
14.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1994
2.62 IPS |
|
|
Style Transfer (F16)
|
100% |
1990
2.62 IPS |
|
|
Style Transfer (I8)
|
98% |
3818
5.02 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
696
24.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
679
24.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1620
57.9 IPS |
|
|
Text Classification (F32)
|
100% |
492
707.2 IPS |
|
|
Text Classification (F16)
|
100% |
532
764.2 IPS |
|
|
Text Classification (I8)
|
92% |
347
499.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1148
21.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1123
20.7 IPS |
|
|
Machine Translation (I8)
|
64% |
393
7.24 IPS |
