HP Victus by HP Gaming Laptop 15-fb0xxx
Geekbench AI Score
2690
Single Precision Score
1294
Half Precision Score
4323
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | December 17 2025 08:38 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 5 5600H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | HP Victus by HP Gaming Laptop 15-fb0xxx |
| Motherboard | HP 8A3F |
| 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 |
| Memory Information | |
|---|---|
| Size | 20.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2195
408.1 IPS |
|
|
Image Classification (HP)
|
100% |
490
91.2 IPS |
|
|
Image Classification (Q)
|
96% |
3925
732.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1298
21.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
718
11.6 IPS |
|
|
Image Segmentation (Q)
|
97% |
4428
72.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3913
4.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
3281
3.83 IPS |
|
|
Pose Estimation (Q)
|
86% |
8479
10.0 IPS |
|
|
Object Detection (SP)
|
100% |
2129
168.9 IPS |
|
|
Object Detection (HP)
|
100% |
633
50.2 IPS |
|
|
Object Detection (Q)
|
58% |
2680
292.8 IPS |
|
|
Face Detection (SP)
|
100% |
2621
31.1 IPS |
|
|
Face Detection (HP)
|
100% |
1206
14.3 IPS |
|
|
Face Detection (Q)
|
96% |
6103
72.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5712
44.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1820
14.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
8005
63.9 IPS |
|
|
Style Transfer (SP)
|
100% |
9955
12.8 IPS |
|
|
Style Transfer (HP)
|
100% |
8374
10.8 IPS |
|
|
Style Transfer (Q)
|
87% |
11155
14.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1824
67.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1678
62.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3307
122.5 IPS |
|
|
Text Classification (SP)
|
100% |
1689
2.25 KIPS |
|
|
Text Classification (HP)
|
100% |
827
1.10 KIPS |
|
|
Text Classification (Q)
|
97% |
1347
1.80 KIPS |
|
|
Machine Translation (SP)
|
100% |
1825
31.4 IPS |
|
|
Machine Translation (HP)
|
100% |
707
12.2 IPS |
|
|
Machine Translation (Q)
|
68% |
2380
46.0 IPS |
