HONOR NMH-WCX9
Geekbench AI Score
675
Single Precision Score
703
Half Precision Score
444
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | dastuchar |
| Upload Date | October 03 2025 07:40 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 5 5500U |
| System Information | |
|---|---|
| Operating System | Arch Linux |
| Model | HONOR NMH-WCX9 |
| Motherboard | HONOR NMH-WCX9-PCB |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 5500U |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 23 Model 104 Stepping 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 7.09 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
370
68.7 IPS |
|
|
Image Classification (HP)
|
100% |
506
94.1 IPS |
|
|
Image Classification (Q)
|
99% |
268
50.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
504
8.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
518
8.39 IPS |
|
|
Image Segmentation (Q)
|
98% |
315
5.13 IPS |
|
|
Pose Estimation (SP)
|
100% |
974
1.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
966
1.13 IPS |
|
|
Pose Estimation (Q)
|
96% |
863
1.01 IPS |
|
|
Object Detection (SP)
|
100% |
500
39.7 IPS |
|
|
Object Detection (HP)
|
100% |
489
38.8 IPS |
|
|
Object Detection (Q)
|
85% |
290
23.3 IPS |
|
|
Face Detection (SP)
|
100% |
815
9.69 IPS |
|
|
Face Detection (HP)
|
100% |
898
10.7 IPS |
|
|
Face Detection (Q)
|
97% |
757
9.03 IPS |
|
|
Depth Estimation (SP)
|
100% |
883
6.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
871
6.71 IPS |
|
|
Depth Estimation (Q)
|
63% |
577
5.41 IPS |
|
|
Style Transfer (SP)
|
100% |
1232
1.58 IPS |
|
|
Style Transfer (HP)
|
100% |
1236
1.59 IPS |
|
|
Style Transfer (Q)
|
98% |
1711
2.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
543
20.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
542
20.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
475
17.6 IPS |
|
|
Text Classification (SP)
|
100% |
489
652.3 IPS |
|
|
Text Classification (HP)
|
100% |
490
653.7 IPS |
|
|
Text Classification (Q)
|
92% |
175
235.5 IPS |
|
|
Machine Translation (SP)
|
100% |
922
15.9 IPS |
|
|
Machine Translation (HP)
|
100% |
933
16.1 IPS |
|
|
Machine Translation (Q)
|
58% |
229
5.38 IPS |
