HONOR BVL-N49
Geekbench ML Score
1205
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:09 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% |
819
153.3 IPS |
|
|
Image Classification (F16)
|
100% |
1295
242.3 IPS |
|
|
Image Classification (I8)
|
99% |
1236
231.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
827
13.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1269
21.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1041
17.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1061
1.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
2492
3.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
2462
2.98 IPS |
|
|
Object Detection (F32)
|
100% |
284
21.2 IPS |
|
|
Object Detection (F16)
|
100% |
562
41.9 IPS |
|
|
Object Detection (I8)
|
62% |
383
28.6 IPS |
|
|
Face Detection (F32)
|
100% |
2622
31.2 IPS |
|
|
Face Detection (F16)
|
97% |
4422
52.6 IPS |
|
|
Face Detection (I8)
|
86% |
3482
41.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1843
14.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
3853
29.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
3702
28.7 IPS |
|
|
Style Transfer (F32)
|
100% |
5256
6.91 IPS |
|
|
Style Transfer (F16)
|
100% |
7831
10.3 IPS |
|
|
Style Transfer (I8)
|
98% |
7809
10.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
416
14.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1439
51.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
714
25.5 IPS |
|
|
Text Classification (F32)
|
100% |
258
370.9 IPS |
|
|
Text Classification (F16)
|
100% |
259
372.4 IPS |
|
|
Text Classification (I8)
|
92% |
425
610.1 IPS |
|
|
Machine Translation (F32)
|
100% |
475
8.73 IPS |
|
|
Machine Translation (F16)
|
100% |
477
8.77 IPS |
|
|
Machine Translation (I8)
|
64% |
512
9.43 IPS |
