Hewlett-Packard HP ProDesk 490 G1 MT
Geekbench AI Score
1187
Single Precision Score
434
Half Precision Score
1543
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | raska-vilem |
| Upload Date | December 04 2025 09:33 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-4570 |
| System Information | |
|---|---|
| Operating System | Pop!_OS 22.04 LTS |
| Model | Hewlett-Packard HP ProDesk 490 G1 MT |
| Motherboard | Hewlett-Packard 18EB |
| CPU Information | |
|---|---|
| Name | Intel Core i5-4570 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 19.46 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
746
138.7 IPS |
|
|
Image Classification (HP)
|
100% |
110
20.4 IPS |
|
|
Image Classification (Q)
|
94% |
1191
222.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
472
7.66 IPS |
|
|
Image Segmentation (HP)
|
100% |
156
2.53 IPS |
|
|
Image Segmentation (Q)
|
98% |
931
15.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2274
2.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
1865
2.18 IPS |
|
|
Pose Estimation (Q)
|
86% |
2403
2.84 IPS |
|
|
Object Detection (SP)
|
100% |
679
53.8 IPS |
|
|
Object Detection (HP)
|
100% |
142
11.2 IPS |
|
|
Object Detection (Q)
|
58% |
878
96.0 IPS |
|
|
Face Detection (SP)
|
100% |
921
10.9 IPS |
|
|
Face Detection (HP)
|
100% |
202
2.40 IPS |
|
|
Face Detection (Q)
|
96% |
2843
33.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2328
17.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
580
4.47 IPS |
|
|
Depth Estimation (Q)
|
78% |
2728
21.8 IPS |
|
|
Style Transfer (SP)
|
100% |
4945
6.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4365
5.61 IPS |
|
|
Style Transfer (Q)
|
87% |
4656
6.06 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
968
35.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
861
31.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1094
40.5 IPS |
|
|
Text Classification (SP)
|
100% |
1100
1.47 KIPS |
|
|
Text Classification (HP)
|
100% |
373
497.6 IPS |
|
|
Text Classification (Q)
|
97% |
776
1.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
909
15.7 IPS |
|
|
Machine Translation (HP)
|
100% |
320
5.52 IPS |
|
|
Machine Translation (Q)
|
68% |
1070
20.7 IPS |
