HONOR BVL-N49
Geekbench ML Score
425
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:14 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
191
35.8 IPS |
|
|
Image Classification (F16)
|
100% |
191
35.7 IPS |
|
|
Image Classification (I8)
|
97% |
483
90.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
238
3.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
239
3.99 IPS |
|
|
Image Segmentation (I8)
|
98% |
480
8.02 IPS |
|
|
Pose Estimation (F32)
|
100% |
328
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
331
0.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1269
1.54 IPS |
|
|
Object Detection (F32)
|
100% |
196
14.6 IPS |
|
|
Object Detection (F16)
|
100% |
198
14.8 IPS |
|
|
Object Detection (I8)
|
61% |
515
38.4 IPS |
|
|
Face Detection (F32)
|
100% |
492
5.86 IPS |
|
|
Face Detection (F16)
|
100% |
490
5.83 IPS |
|
|
Face Detection (I8)
|
86% |
1093
13.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
428
3.32 IPS |
|
|
Depth Estimation (F16)
|
100% |
426
3.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
1142
8.85 IPS |
|
|
Style Transfer (F32)
|
100% |
694
0.91 IPS |
|
|
Style Transfer (F16)
|
100% |
690
0.91 IPS |
|
|
Style Transfer (I8)
|
98% |
1637
2.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
228
8.14 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
231
8.26 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
772
27.6 IPS |
|
|
Text Classification (F32)
|
100% |
257
369.7 IPS |
|
|
Text Classification (F16)
|
100% |
261
375.5 IPS |
|
|
Text Classification (I8)
|
92% |
426
612.2 IPS |
|
|
Machine Translation (F32)
|
100% |
472
8.69 IPS |
|
|
Machine Translation (F16)
|
100% |
477
8.78 IPS |
|
|
Machine Translation (I8)
|
64% |
507
9.33 IPS |
