Hewlett-Packard HP ProDesk 600 G1 SFF
Geekbench AI Score
1098
Single Precision Score
603
Half Precision Score
1235
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | langa |
| Upload Date | September 23 2025 10:17 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-4570 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Hewlett-Packard HP ProDesk 600 G1 SFF |
| Motherboard | Hewlett-Packard 18E7 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-4570 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
814
151.3 IPS |
|
|
Image Classification (HP)
|
100% |
236
43.9 IPS |
|
|
Image Classification (Q)
|
96% |
939
175.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
425
6.89 IPS |
|
|
Image Segmentation (HP)
|
100% |
328
5.32 IPS |
|
|
Image Segmentation (Q)
|
97% |
944
15.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1892
2.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
1570
1.83 IPS |
|
|
Pose Estimation (Q)
|
86% |
2345
2.77 IPS |
|
|
Object Detection (SP)
|
100% |
689
54.7 IPS |
|
|
Object Detection (HP)
|
100% |
295
23.4 IPS |
|
|
Object Detection (Q)
|
58% |
652
71.3 IPS |
|
|
Face Detection (SP)
|
100% |
1291
15.3 IPS |
|
|
Face Detection (HP)
|
100% |
579
6.88 IPS |
|
|
Face Detection (Q)
|
96% |
2162
25.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2198
16.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
891
6.86 IPS |
|
|
Depth Estimation (Q)
|
78% |
2421
19.3 IPS |
|
|
Style Transfer (SP)
|
100% |
4390
5.64 IPS |
|
|
Style Transfer (HP)
|
100% |
3703
4.76 IPS |
|
|
Style Transfer (Q)
|
87% |
4234
5.51 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
822
30.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
720
26.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1156
42.8 IPS |
|
|
Text Classification (SP)
|
100% |
789
1.05 KIPS |
|
|
Text Classification (HP)
|
100% |
393
524.1 IPS |
|
|
Text Classification (Q)
|
97% |
274
367.7 IPS |
|
|
Machine Translation (SP)
|
100% |
702
12.1 IPS |
|
|
Machine Translation (HP)
|
100% |
330
5.69 IPS |
|
|
Machine Translation (Q)
|
68% |
869
16.8 IPS |
