HP Victus by HP Laptop 16-e1xxx
Geekbench AI Score
2279
Single Precision Score
1181
Half Precision Score
3841
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | minhle |
| Upload Date | January 27 2025 09:58 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 5 6600H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | HP Victus by HP Laptop 16-e1xxx |
| Motherboard | HP 8A22 |
| Power Plan | Balanced |
| 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% |
1827
339.7 IPS |
|
|
Image Classification (HP)
|
100% |
489
90.9 IPS |
|
|
Image Classification (Q)
|
96% |
3820
713.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
567
9.19 IPS |
|
|
Image Segmentation (HP)
|
100% |
429
6.96 IPS |
|
|
Image Segmentation (Q)
|
97% |
2247
36.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
3800
4.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
3251
3.79 IPS |
|
|
Pose Estimation (Q)
|
86% |
8589
10.2 IPS |
|
|
Object Detection (SP)
|
100% |
1462
116.0 IPS |
|
|
Object Detection (HP)
|
100% |
605
48.0 IPS |
|
|
Object Detection (Q)
|
58% |
2166
236.6 IPS |
|
|
Face Detection (SP)
|
100% |
3672
43.6 IPS |
|
|
Face Detection (HP)
|
100% |
1255
14.9 IPS |
|
|
Face Detection (Q)
|
96% |
6519
77.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5084
39.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
1879
14.5 IPS |
|
|
Depth Estimation (Q)
|
78% |
8203
65.5 IPS |
|
|
Style Transfer (SP)
|
100% |
9307
12.0 IPS |
|
|
Style Transfer (HP)
|
100% |
8160
10.5 IPS |
|
|
Style Transfer (Q)
|
87% |
13001
16.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1639
60.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1544
57.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2250
83.4 IPS |
|
|
Text Classification (SP)
|
100% |
1432
1.91 KIPS |
|
|
Text Classification (HP)
|
100% |
711
949.3 IPS |
|
|
Text Classification (Q)
|
97% |
1444
1.93 KIPS |
|
|
Machine Translation (SP)
|
100% |
1613
27.8 IPS |
|
|
Machine Translation (HP)
|
100% |
607
10.5 IPS |
|
|
Machine Translation (Q)
|
68% |
1938
37.5 IPS |
