HP HP ProDesk 600 G3 SFF
Geekbench AI Score
766
Single Precision Score
460
Half Precision Score
874
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Graha |
| Upload Date | December 04 2024 03:31 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i3-7100 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | HP HP ProDesk 600 G3 SFF |
| Motherboard | HP 82B4 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i3-7100 |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 9 |
| Base Frequency | 3.91 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
495
92.1 IPS |
|
|
Image Classification (HP)
|
100% |
219
40.7 IPS |
|
|
Image Classification (Q)
|
96% |
732
136.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
370
6.00 IPS |
|
|
Image Segmentation (HP)
|
100% |
312
5.06 IPS |
|
|
Image Segmentation (Q)
|
97% |
587
9.54 IPS |
|
|
Pose Estimation (SP)
|
100% |
1285
1.50 IPS |
|
|
Pose Estimation (HP)
|
100% |
1017
1.19 IPS |
|
|
Pose Estimation (Q)
|
87% |
1768
2.09 IPS |
|
|
Object Detection (SP)
|
100% |
334
26.5 IPS |
|
|
Object Detection (HP)
|
100% |
169
13.4 IPS |
|
|
Object Detection (Q)
|
86% |
361
29.0 IPS |
|
|
Face Detection (SP)
|
100% |
664
7.89 IPS |
|
|
Face Detection (HP)
|
100% |
380
4.52 IPS |
|
|
Face Detection (Q)
|
96% |
980
11.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1108
8.54 IPS |
|
|
Depth Estimation (HP)
|
99% |
723
5.57 IPS |
|
|
Depth Estimation (Q)
|
77% |
1329
10.6 IPS |
|
|
Style Transfer (SP)
|
100% |
3210
4.13 IPS |
|
|
Style Transfer (HP)
|
100% |
2411
3.10 IPS |
|
|
Style Transfer (Q)
|
87% |
4147
5.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
673
24.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
536
19.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
918
34.0 IPS |
|
|
Text Classification (SP)
|
100% |
659
879.2 IPS |
|
|
Text Classification (HP)
|
100% |
335
447.8 IPS |
|
|
Text Classification (Q)
|
97% |
285
382.1 IPS |
|
|
Machine Translation (SP)
|
100% |
854
14.7 IPS |
|
|
Machine Translation (HP)
|
100% |
304
5.24 IPS |
|
|
Machine Translation (Q)
|
60% |
677
15.1 IPS |
