HONOR VER-N49
Geekbench ML Score
1073
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 17 2024 09:13 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | HONOR VER-N49 |
| Model ID | HONOR VER-N49 |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 14.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
615
115.0 IPS |
|
|
Image Classification (F16)
|
100% |
1020
190.9 IPS |
|
|
Image Classification (I8)
|
99% |
971
181.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1220
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1943
32.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1852
30.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
930
1.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
1384
1.68 IPS |
|
|
Pose Estimation (I8)
|
100% |
1382
1.67 IPS |
|
|
Object Detection (F32)
|
100% |
397
29.7 IPS |
|
|
Object Detection (F16)
|
100% |
573
42.8 IPS |
|
|
Object Detection (I8)
|
62% |
498
37.2 IPS |
|
|
Face Detection (F32)
|
100% |
2116
25.2 IPS |
|
|
Face Detection (F16)
|
97% |
3377
40.2 IPS |
|
|
Face Detection (I8)
|
86% |
2980
35.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1438
11.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2752
21.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
2717
21.1 IPS |
|
|
Style Transfer (F32)
|
100% |
3583
4.71 IPS |
|
|
Style Transfer (F16)
|
100% |
8061
10.6 IPS |
|
|
Style Transfer (I8)
|
98% |
8087
10.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
470
16.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
418
14.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
413
14.7 IPS |
|
|
Text Classification (F32)
|
100% |
327
470.5 IPS |
|
|
Text Classification (F16)
|
100% |
326
468.9 IPS |
|
|
Text Classification (I8)
|
92% |
201
289.5 IPS |
|
|
Machine Translation (F32)
|
100% |
556
10.2 IPS |
|
|
Machine Translation (F16)
|
100% |
557
10.3 IPS |
|
|
Machine Translation (I8)
|
64% |
545
10.0 IPS |
