HP HP ProDesk 600 G2 SFF
Geekbench AI Score
1354
Single Precision Score
671
Half Precision Score
1662
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | ttam |
| Upload Date | December 06 2024 12:49 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-6500 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 (64-bit) |
| Model | HP HP ProDesk 600 G2 SFF |
| Motherboard | HP 805D |
| CPU Information | |
|---|---|
| Name | Intel Core i5-6500 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 3.19 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1043
193.9 IPS |
|
|
Image Classification (HP)
|
100% |
261
48.5 IPS |
|
|
Image Classification (Q)
|
96% |
1449
270.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
540
8.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
376
6.10 IPS |
|
|
Image Segmentation (Q)
|
97% |
885
14.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2179
2.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
1765
2.06 IPS |
|
|
Pose Estimation (Q)
|
86% |
3993
4.72 IPS |
|
|
Object Detection (SP)
|
100% |
956
75.8 IPS |
|
|
Object Detection (HP)
|
100% |
286
22.7 IPS |
|
|
Object Detection (Q)
|
58% |
1029
112.4 IPS |
|
|
Face Detection (SP)
|
100% |
1650
19.6 IPS |
|
|
Face Detection (HP)
|
100% |
655
7.78 IPS |
|
|
Face Detection (Q)
|
96% |
2942
35.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2772
21.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
968
7.46 IPS |
|
|
Depth Estimation (Q)
|
78% |
3709
29.6 IPS |
|
|
Style Transfer (SP)
|
100% |
5217
6.71 IPS |
|
|
Style Transfer (HP)
|
100% |
4191
5.39 IPS |
|
|
Style Transfer (Q)
|
87% |
6590
8.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1015
37.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
859
31.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1359
50.3 IPS |
|
|
Text Classification (SP)
|
100% |
791
1.06 KIPS |
|
|
Text Classification (HP)
|
100% |
448
597.5 IPS |
|
|
Text Classification (Q)
|
97% |
306
410.4 IPS |
|
|
Machine Translation (SP)
|
100% |
925
15.9 IPS |
|
|
Machine Translation (HP)
|
100% |
368
6.34 IPS |
|
|
Machine Translation (Q)
|
68% |
1021
19.7 IPS |
