HONOR BVL-N49
Geekbench ML Score
925
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:06 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% |
480
89.9 IPS |
|
|
Image Classification (F16)
|
100% |
446
83.4 IPS |
|
|
Image Classification (I8)
|
97% |
728
136.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
601
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
603
10.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
610
10.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1154
1.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
1119
1.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
4418
5.35 IPS |
|
|
Object Detection (F32)
|
100% |
472
35.2 IPS |
|
|
Object Detection (F16)
|
100% |
471
35.2 IPS |
|
|
Object Detection (I8)
|
61% |
886
66.2 IPS |
|
|
Face Detection (F32)
|
100% |
1160
13.8 IPS |
|
|
Face Detection (F16)
|
100% |
1145
13.6 IPS |
|
|
Face Detection (I8)
|
86% |
1820
21.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1084
8.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
1071
8.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
1812
14.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1908
2.51 IPS |
|
|
Style Transfer (F16)
|
100% |
1952
2.57 IPS |
|
|
Style Transfer (I8)
|
98% |
3845
5.06 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
686
24.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
701
25.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1595
57.0 IPS |
|
|
Text Classification (F32)
|
100% |
464
667.0 IPS |
|
|
Text Classification (F16)
|
100% |
519
746.3 IPS |
|
|
Text Classification (I8)
|
92% |
350
503.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1145
21.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1149
21.1 IPS |
|
|
Machine Translation (I8)
|
64% |
415
7.64 IPS |
