Hewlett-Packard HP ProDesk 400 G1 MT
Geekbench AI Score
1432
Single Precision Score
733
Half Precision Score
1670
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | fenom |
| Upload Date | October 22 2025 03:22 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-4770 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Hewlett-Packard HP ProDesk 400 G1 MT |
| Motherboard | Hewlett-Packard 198E |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-4770 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1112
206.8 IPS |
|
|
Image Classification (HP)
|
100% |
292
54.3 IPS |
|
|
Image Classification (Q)
|
96% |
1181
220.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
613
9.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
428
6.94 IPS |
|
|
Image Segmentation (Q)
|
97% |
1493
24.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2234
2.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
1875
2.19 IPS |
|
|
Pose Estimation (Q)
|
86% |
2532
2.99 IPS |
|
|
Object Detection (SP)
|
100% |
983
78.0 IPS |
|
|
Object Detection (HP)
|
100% |
367
29.1 IPS |
|
|
Object Detection (Q)
|
58% |
895
97.8 IPS |
|
|
Face Detection (SP)
|
100% |
1857
22.1 IPS |
|
|
Face Detection (HP)
|
100% |
736
8.74 IPS |
|
|
Face Detection (Q)
|
96% |
2768
33.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2852
22.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1043
8.04 IPS |
|
|
Depth Estimation (Q)
|
78% |
2967
23.7 IPS |
|
|
Style Transfer (SP)
|
100% |
5210
6.70 IPS |
|
|
Style Transfer (HP)
|
100% |
4200
5.40 IPS |
|
|
Style Transfer (Q)
|
87% |
5175
6.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
944
34.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
828
30.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1293
47.9 IPS |
|
|
Text Classification (SP)
|
100% |
1007
1.34 KIPS |
|
|
Text Classification (HP)
|
100% |
470
627.5 IPS |
|
|
Text Classification (Q)
|
97% |
668
895.2 IPS |
|
|
Machine Translation (SP)
|
100% |
927
16.0 IPS |
|
|
Machine Translation (HP)
|
100% |
418
7.19 IPS |
|
|
Machine Translation (Q)
|
68% |
1152
22.3 IPS |
