HONOR HYM-WXX
Geekbench ML Score
2141
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | June 16 2025 01:42 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | HONOR HYM-WXX |
| Motherboard | HONOR HYM-WXX-PCB |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 5600H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 512 KB x 6 |
| 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% |
1205
225.4 IPS |
|
|
Image Classification (F16)
|
100% |
1196
223.7 IPS |
|
|
Image Classification (I8)
|
97% |
2269
424.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
908
15.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
961
16.0 IPS |
|
|
Image Segmentation (I8)
|
97% |
1848
30.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
3134
3.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
3364
4.07 IPS |
|
|
Pose Estimation (I8)
|
100% |
8067
9.77 IPS |
|
|
Object Detection (F32)
|
100% |
1289
96.3 IPS |
|
|
Object Detection (F16)
|
100% |
1279
95.5 IPS |
|
|
Object Detection (I8)
|
60% |
1137
84.9 IPS |
|
|
Face Detection (F32)
|
100% |
1268
15.1 IPS |
|
|
Face Detection (F16)
|
100% |
1279
15.2 IPS |
|
|
Face Detection (I8)
|
87% |
2437
29.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3803
29.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
3713
28.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
7327
56.8 IPS |
|
|
Style Transfer (F32)
|
100% |
8543
11.2 IPS |
|
|
Style Transfer (F16)
|
100% |
8003
10.5 IPS |
|
|
Style Transfer (I8)
|
85% |
9247
12.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1637
58.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1662
59.4 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2017
72.0 IPS |
|
|
Text Classification (F32)
|
100% |
1515
2.18 KIPS |
|
|
Text Classification (F16)
|
100% |
1499
2.15 KIPS |
|
|
Text Classification (I8)
|
94% |
1026
1.47 KIPS |
|
|
Machine Translation (F32)
|
100% |
1289
23.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1344
24.7 IPS |
|
|
Machine Translation (I8)
|
67% |
1725
31.7 IPS |
