HP OMEN 30L Desktop GT13-0xxx
Geekbench AI Score
3793
Single Precision Score
1539
Half Precision Score
5023
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | samuelks |
| Upload Date | January 29 2025 11:42 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i9-10850K |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | HP OMEN 30L Desktop GT13-0xxx |
| Motherboard | HP 8703 |
| Power Plan | HP Recommended |
| CPU Information | |
|---|---|
| Name | Intel Core i9-10850K |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3073
571.4 IPS |
|
|
Image Classification (HP)
|
100% |
529
98.3 IPS |
|
|
Image Classification (Q)
|
96% |
4956
925.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1845
29.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
833
13.5 IPS |
|
|
Image Segmentation (Q)
|
97% |
2555
41.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6657
7.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
5754
6.71 IPS |
|
|
Pose Estimation (Q)
|
86% |
13901
16.4 IPS |
|
|
Object Detection (SP)
|
100% |
2907
230.6 IPS |
|
|
Object Detection (HP)
|
100% |
677
53.7 IPS |
|
|
Object Detection (Q)
|
58% |
3544
387.2 IPS |
|
|
Face Detection (SP)
|
100% |
4470
53.1 IPS |
|
|
Face Detection (HP)
|
100% |
1394
16.6 IPS |
|
|
Face Detection (Q)
|
96% |
7791
92.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8388
64.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2162
16.7 IPS |
|
|
Depth Estimation (Q)
|
78% |
10748
85.8 IPS |
|
|
Style Transfer (SP)
|
100% |
16818
21.6 IPS |
|
|
Style Transfer (HP)
|
100% |
13568
17.4 IPS |
|
|
Style Transfer (Q)
|
87% |
16677
21.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2851
105.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2159
79.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3311
122.7 IPS |
|
|
Text Classification (SP)
|
100% |
1566
2.09 KIPS |
|
|
Text Classification (HP)
|
100% |
741
989.7 IPS |
|
|
Text Classification (Q)
|
97% |
1364
1.83 KIPS |
|
|
Machine Translation (SP)
|
100% |
1996
34.4 IPS |
|
|
Machine Translation (HP)
|
100% |
665
11.4 IPS |
|
|
Machine Translation (Q)
|
68% |
2600
50.2 IPS |
