HONOR HYM-WXX
Geekbench ML Score
2207
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 17 2024 05:49 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 IoT Enterprise LTSC (64-bit) |
| Model | HONOR HYM-WXX |
| Motherboard | HONOR HYM-WXX-PCB |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5800H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 512 KB x 8 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1328
248.4 IPS |
|
|
Image Classification (F16)
|
100% |
1312
245.4 IPS |
|
|
Image Classification (I8)
|
97% |
2353
440.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1222
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1214
20.3 IPS |
|
|
Image Segmentation (I8)
|
97% |
1563
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
3842
4.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
3790
4.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
7958
9.64 IPS |
|
|
Object Detection (F32)
|
100% |
1184
88.4 IPS |
|
|
Object Detection (F16)
|
100% |
1244
92.9 IPS |
|
|
Object Detection (I8)
|
60% |
1240
92.6 IPS |
|
|
Face Detection (F32)
|
100% |
1419
16.9 IPS |
|
|
Face Detection (F16)
|
100% |
1405
16.7 IPS |
|
|
Face Detection (I8)
|
87% |
2727
32.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
4371
33.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
4398
34.1 IPS |
|
|
Depth Estimation (I8)
|
74% |
7548
58.5 IPS |
|
|
Style Transfer (F32)
|
100% |
8590
11.3 IPS |
|
|
Style Transfer (F16)
|
100% |
9005
11.8 IPS |
|
|
Style Transfer (I8)
|
85% |
9918
13.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1914
68.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1893
67.6 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2216
79.1 IPS |
|
|
Text Classification (F32)
|
100% |
1350
1.94 KIPS |
|
|
Text Classification (F16)
|
100% |
1351
1.94 KIPS |
|
|
Text Classification (I8)
|
94% |
335
481.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1503
27.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1442
26.5 IPS |
|
|
Machine Translation (I8)
|
67% |
1594
29.3 IPS |
