HP OMEN 30L Desktop GT13-0xxx - DevRTX-30 HP OMEN 30L Desktop GT13-0xxx
Geekbench AI Score
19821
Single Precision Score
27898
Half Precision Score
12850
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | RootsGTA |
| Upload Date | March 06 2025 12:06 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | HP OMEN 30L Desktop GT13-0xxx |
| Motherboard | HP 8703 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10700KF |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7663
1.43 KIPS |
|
|
Image Classification (HP)
|
99% |
10793
2.01 KIPS |
|
|
Image Classification (Q)
|
100% |
5661
1.05 KIPS |
|
|
Image Segmentation (SP)
|
100% |
10432
169.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
13074
211.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
8478
137.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
157700
184.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
309440
361.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
117953
138.2 IPS |
|
|
Object Detection (SP)
|
100% |
10079
799.5 IPS |
|
|
Object Detection (HP)
|
100% |
13227
1.05 KIPS |
|
|
Object Detection (Q)
|
85% |
7058
567.8 IPS |
|
|
Face Detection (SP)
|
100% |
25060
297.8 IPS |
|
|
Face Detection (HP)
|
100% |
30683
364.6 IPS |
|
|
Face Detection (Q)
|
97% |
17451
208.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
57098
439.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
89514
689.6 IPS |
|
|
Depth Estimation (Q)
|
77% |
34994
280.2 IPS |
|
|
Style Transfer (SP)
|
100% |
238871
307.1 IPS |
|
|
Style Transfer (HP)
|
100% |
529803
681.1 IPS |
|
|
Style Transfer (Q)
|
98% |
175325
226.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
32363
1.20 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
44054
1.63 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
19547
723.8 IPS |
|
|
Text Classification (SP)
|
100% |
2408
3.21 KIPS |
|
|
Text Classification (HP)
|
99% |
2824
3.77 KIPS |
|
|
Text Classification (Q)
|
97% |
1183
1.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
2766
47.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2732
47.1 IPS |
|
|
Machine Translation (Q)
|
70% |
1241
23.3 IPS |
