HONOR BVL-N49
Geekbench ML Score
1176
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 20 2024 11:21 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
836
156.5 IPS |
|
|
Image Classification (F16)
|
100% |
1327
248.4 IPS |
|
|
Image Classification (I8)
|
99% |
1231
230.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
832
13.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1258
21.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1198
20.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1059
1.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
2484
3.01 IPS |
|
|
Pose Estimation (I8)
|
100% |
2484
3.01 IPS |
|
|
Object Detection (F32)
|
100% |
256
19.1 IPS |
|
|
Object Detection (F16)
|
100% |
268
20.0 IPS |
|
|
Object Detection (I8)
|
62% |
264
19.7 IPS |
|
|
Face Detection (F32)
|
100% |
2615
31.1 IPS |
|
|
Face Detection (F16)
|
97% |
4244
50.5 IPS |
|
|
Face Detection (I8)
|
86% |
3726
44.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1825
14.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
3715
28.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
3710
28.8 IPS |
|
|
Style Transfer (F32)
|
100% |
5227
6.88 IPS |
|
|
Style Transfer (F16)
|
100% |
7784
10.2 IPS |
|
|
Style Transfer (I8)
|
98% |
7871
10.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
417
14.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
748
26.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1353
48.3 IPS |
|
|
Text Classification (F32)
|
100% |
280
402.3 IPS |
|
|
Text Classification (F16)
|
100% |
282
406.0 IPS |
|
|
Text Classification (I8)
|
92% |
446
641.6 IPS |
|
|
Machine Translation (F32)
|
100% |
497
9.14 IPS |
|
|
Machine Translation (F16)
|
100% |
494
9.10 IPS |
|
|
Machine Translation (I8)
|
64% |
539
9.92 IPS |
