HONOR GOH-X
Geekbench AI Score
3973
Single Precision Score
4751
Half Precision Score
3060
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | Diagonal |
| Upload Date | December 08 2025 03:42 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon(TM) Graphics |
| System Information | |
|---|---|
| Operating System | Windows 11 (64-bit) |
| Model | HONOR GOH-X |
| Motherboard | HONOR GOH-X-PCB |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 6600H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 68 Stepping 1 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1373
255.4 IPS |
|
|
Image Classification (HP)
|
100% |
1623
301.8 IPS |
|
|
Image Classification (Q)
|
100% |
1241
230.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2504
40.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1777
28.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
2020
32.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
15673
18.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
27116
31.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
13306
15.6 IPS |
|
|
Object Detection (SP)
|
100% |
1560
123.8 IPS |
|
|
Object Detection (HP)
|
100% |
1567
124.3 IPS |
|
|
Object Detection (Q)
|
87% |
1387
111.4 IPS |
|
|
Face Detection (SP)
|
100% |
4050
48.1 IPS |
|
|
Face Detection (HP)
|
100% |
5296
62.9 IPS |
|
|
Face Detection (Q)
|
97% |
3341
39.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8360
64.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
10565
81.6 IPS |
|
|
Depth Estimation (Q)
|
77% |
6725
53.9 IPS |
|
|
Style Transfer (SP)
|
100% |
26911
34.6 IPS |
|
|
Style Transfer (HP)
|
100% |
38813
49.9 IPS |
|
|
Style Transfer (Q)
|
98% |
22021
28.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5835
215.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8290
306.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4137
153.2 IPS |
|
|
Text Classification (SP)
|
100% |
1089
1.45 KIPS |
|
|
Text Classification (HP)
|
100% |
1360
1.81 KIPS |
|
|
Text Classification (Q)
|
97% |
754
1.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
2015
34.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1956
33.7 IPS |
|
|
Machine Translation (Q)
|
70% |
1010
18.9 IPS |
