HP HP ProDesk 600 G3 SFF
Geekbench AI Score
1231
Single Precision Score
1834
Half Precision Score
1723
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Graha |
| Upload Date | December 18 2024 07:58 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) HD Graphics 630 (iGPU) |
| 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% |
786
146.1 IPS |
|
|
Image Classification (HP)
|
100% |
1276
237.2 IPS |
|
|
Image Classification (Q)
|
100% |
1158
215.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1001
16.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1610
26.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
1500
24.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1868
2.18 IPS |
|
|
Pose Estimation (HP)
|
99% |
1988
2.33 IPS |
|
|
Pose Estimation (Q)
|
97% |
2655
3.11 IPS |
|
|
Object Detection (SP)
|
100% |
718
56.9 IPS |
|
|
Object Detection (HP)
|
99% |
1225
97.4 IPS |
|
|
Object Detection (Q)
|
88% |
1149
92.2 IPS |
|
|
Face Detection (SP)
|
100% |
2149
25.5 IPS |
|
|
Face Detection (HP)
|
100% |
3684
43.8 IPS |
|
|
Face Detection (Q)
|
97% |
3301
39.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
2271
17.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
3938
30.4 IPS |
|
|
Depth Estimation (Q)
|
89% |
3573
27.8 IPS |
|
|
Style Transfer (SP)
|
100% |
5297
6.81 IPS |
|
|
Style Transfer (HP)
|
100% |
7170
9.22 IPS |
|
|
Style Transfer (Q)
|
98% |
6417
8.28 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
946
34.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1687
62.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1620
60.0 IPS |
|
|
Text Classification (SP)
|
71% |
496
717.2 IPS |
|
|
Text Classification (HP)
|
71% |
579
837.3 IPS |
|
|
Text Classification (Q)
|
92% |
421
565.2 IPS |
|
|
Machine Translation (SP)
|
100% |
628
10.8 IPS |
|
|
Machine Translation (HP)
|
97% |
848
14.7 IPS |
|
|
Machine Translation (Q)
|
98% |
847
14.6 IPS |
