HP Victus by HP Laptop 16-d1xxx
Geekbench AI Score
10230
Single Precision Score
19461
Half Precision Score
7101
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | July 09 2025 09:24 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3050 Ti Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | HP Victus by HP Laptop 16-d1xxx |
| Motherboard | HP 8A26 |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-12700H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4373
813.2 IPS |
|
|
Image Classification (HP)
|
99% |
8015
1.49 KIPS |
|
|
Image Classification (Q)
|
99% |
3574
666.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
6634
107.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
11365
184.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
5434
88.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
40372
47.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
143607
167.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
34228
40.1 IPS |
|
|
Object Detection (SP)
|
100% |
5183
411.1 IPS |
|
|
Object Detection (HP)
|
100% |
10322
818.7 IPS |
|
|
Object Detection (Q)
|
84% |
4146
334.4 IPS |
|
|
Face Detection (SP)
|
100% |
11189
132.9 IPS |
|
|
Face Detection (HP)
|
100% |
19807
235.4 IPS |
|
|
Face Detection (Q)
|
97% |
9108
108.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
23747
183.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
50012
386.4 IPS |
|
|
Depth Estimation (Q)
|
77% |
16996
136.3 IPS |
|
|
Style Transfer (SP)
|
100% |
71768
92.3 IPS |
|
|
Style Transfer (HP)
|
100% |
201731
259.3 IPS |
|
|
Style Transfer (Q)
|
98% |
58416
75.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
15314
565.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27916
1.03 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
9001
333.3 IPS |
|
|
Text Classification (SP)
|
100% |
2312
3.09 KIPS |
|
|
Text Classification (HP)
|
99% |
3256
4.35 KIPS |
|
|
Text Classification (Q)
|
97% |
1129
1.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
3063
52.8 IPS |
|
|
Machine Translation (HP)
|
100% |
3178
54.7 IPS |
|
|
Machine Translation (Q)
|
70% |
1288
24.2 IPS |
