HP OMEN by HP Gaming Laptop 16t-wf100
Geekbench AI Score
3636
Single Precision Score
3602
Half Precision Score
7591
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | giodamuz |
| Upload Date | February 27 2026 05:20 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i7-14700HX |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | HP OMEN by HP Gaming Laptop 16t-wf100 |
| Motherboard | HP 8C77 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-14700HX |
| Topology | 1 Processor, 19 Cores, 27 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 11 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2177
404.9 IPS |
|
|
Image Classification (HP)
|
100% |
1675
311.5 IPS |
|
|
Image Classification (Q)
|
100% |
4115
765.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2763
44.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2808
45.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
4977
80.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
4977
5.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
5002
5.84 IPS |
|
|
Pose Estimation (Q)
|
96% |
17136
20.1 IPS |
|
|
Object Detection (SP)
|
100% |
1900
150.7 IPS |
|
|
Object Detection (HP)
|
100% |
1973
156.5 IPS |
|
|
Object Detection (Q)
|
88% |
4504
361.0 IPS |
|
|
Face Detection (SP)
|
100% |
6276
74.6 IPS |
|
|
Face Detection (HP)
|
100% |
6160
73.2 IPS |
|
|
Face Detection (Q)
|
100% |
10515
124.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5262
40.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
5640
43.5 IPS |
|
|
Depth Estimation (Q)
|
89% |
12599
98.0 IPS |
|
|
Style Transfer (SP)
|
100% |
14130
18.2 IPS |
|
|
Style Transfer (HP)
|
100% |
14047
18.1 IPS |
|
|
Style Transfer (Q)
|
98% |
46277
59.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2696
99.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2748
101.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7246
268.3 IPS |
|
|
Text Classification (SP)
|
100% |
1782
2.38 KIPS |
|
|
Text Classification (HP)
|
100% |
1823
2.43 KIPS |
|
|
Text Classification (Q)
|
92% |
3016
4.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
3172
54.6 IPS |
|
|
Machine Translation (HP)
|
100% |
3241
55.8 IPS |
|
|
Machine Translation (Q)
|
100% |
3001
51.7 IPS |
