HP Victus by HP Laptop 16-e0xxx
Geekbench AI Score
3335
Single Precision Score
3354
Half Precision Score
5962
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | s-goude-surgar |
| Upload Date | October 24 2025 12:47 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 7 5800H with Radeon Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Famille (64-bit) |
| Model | HP Victus by HP Laptop 16-e0xxx |
| Motherboard | HP 88EE |
| Power Plan | Performances leves |
| 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 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2200
409.1 IPS |
|
|
Image Classification (HP)
|
100% |
2393
445.1 IPS |
|
|
Image Classification (Q)
|
100% |
4456
828.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2407
39.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2216
35.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4559
74.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
4196
4.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
4289
5.01 IPS |
|
|
Pose Estimation (Q)
|
94% |
10321
12.1 IPS |
|
|
Object Detection (SP)
|
100% |
1913
151.7 IPS |
|
|
Object Detection (HP)
|
100% |
1919
152.2 IPS |
|
|
Object Detection (Q)
|
87% |
4277
343.0 IPS |
|
|
Face Detection (SP)
|
100% |
3840
45.6 IPS |
|
|
Face Detection (HP)
|
100% |
3995
47.5 IPS |
|
|
Face Detection (Q)
|
97% |
11481
136.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5236
40.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
5050
38.9 IPS |
|
|
Depth Estimation (Q)
|
81% |
10521
83.0 IPS |
|
|
Style Transfer (SP)
|
100% |
12269
15.8 IPS |
|
|
Style Transfer (HP)
|
100% |
13148
16.9 IPS |
|
|
Style Transfer (Q)
|
98% |
31246
40.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2412
89.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2532
93.5 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
5889
218.1 IPS |
|
|
Text Classification (SP)
|
100% |
2218
2.96 KIPS |
|
|
Text Classification (HP)
|
100% |
2089
2.79 KIPS |
|
|
Text Classification (Q)
|
91% |
939
1.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
3042
52.4 IPS |
|
|
Machine Translation (HP)
|
100% |
2945
50.7 IPS |
|
|
Machine Translation (Q)
|
100% |
3033
52.3 IPS |
