HP Victus by HP Gaming Laptop 16-s0xxx
Geekbench AI Score
2296
Single Precision Score
992
Half Precision Score
4144
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 25 2024 08:28 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 7840HS |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | HP Victus by HP Gaming Laptop 16-s0xxx |
| Motherboard | HP 8BD5 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 7840HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 116 Stepping 1 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2138
397.6 IPS |
|
|
Image Classification (HP)
|
100% |
382
71.1 IPS |
|
|
Image Classification (Q)
|
99% |
4502
839.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
719
11.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
484
7.85 IPS |
|
|
Image Segmentation (Q)
|
98% |
2283
37.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
4035
4.71 IPS |
|
|
Pose Estimation (HP)
|
100% |
3436
4.01 IPS |
|
|
Pose Estimation (Q)
|
94% |
17245
20.2 IPS |
|
|
Object Detection (SP)
|
100% |
1930
153.1 IPS |
|
|
Object Detection (HP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (Q)
|
86% |
4179
335.9 IPS |
|
|
Face Detection (SP)
|
100% |
3076
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
908
10.8 IPS |
|
|
Face Detection (Q)
|
97% |
6662
79.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5723
44.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1557
12.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
6033
48.1 IPS |
|
|
Style Transfer (SP)
|
100% |
10197
13.1 IPS |
|
|
Style Transfer (HP)
|
100% |
8581
11.0 IPS |
|
|
Style Transfer (Q)
|
98% |
16130
20.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1460
53.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1310
48.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2017
74.7 IPS |
|
|
Text Classification (SP)
|
100% |
1136
1.52 KIPS |
|
|
Text Classification (HP)
|
100% |
458
611.4 IPS |
|
|
Text Classification (Q)
|
97% |
1081
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
1145
19.7 IPS |
|
|
Machine Translation (HP)
|
100% |
442
7.61 IPS |
|
|
Machine Translation (Q)
|
65% |
1428
28.7 IPS |
