HONOR BVL-N49
Geekbench ML Score
1230
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 25 2024 11:57 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% |
586
109.6 IPS |
|
|
Image Classification (F16)
|
100% |
586
109.6 IPS |
|
|
Image Classification (I8)
|
97% |
1046
195.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
775
12.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
788
13.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
813
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1343
1.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
1343
1.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
5937
7.19 IPS |
|
|
Object Detection (F32)
|
100% |
588
43.9 IPS |
|
|
Object Detection (F16)
|
100% |
588
43.9 IPS |
|
|
Object Detection (I8)
|
61% |
1376
102.7 IPS |
|
|
Face Detection (F32)
|
100% |
1392
16.5 IPS |
|
|
Face Detection (F16)
|
100% |
1381
16.4 IPS |
|
|
Face Detection (I8)
|
86% |
2368
28.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1355
10.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
1401
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2553
19.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2416
3.18 IPS |
|
|
Style Transfer (F16)
|
100% |
2232
2.94 IPS |
|
|
Style Transfer (I8)
|
98% |
5385
7.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
961
34.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
936
33.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2484
88.7 IPS |
|
|
Text Classification (F32)
|
100% |
743
1.07 KIPS |
|
|
Text Classification (F16)
|
100% |
771
1.11 KIPS |
|
|
Text Classification (I8)
|
92% |
547
786.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1483
27.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1400
25.8 IPS |
|
|
Machine Translation (I8)
|
64% |
599
11.0 IPS |
