HP HP ProDesk 600 G3 SFF
Geekbench AI Score
1272
Single Precision Score
1272
Half Precision Score
1908
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Graha |
| Upload Date | December 18 2024 08:52 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i3-7100 CPU @ 3.90GHz |
| 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% |
732
136.2 IPS |
|
|
Image Classification (HP)
|
100% |
731
136.0 IPS |
|
|
Image Classification (Q)
|
100% |
1137
211.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
798
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
794
12.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
1190
19.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1481
1.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
1483
1.73 IPS |
|
|
Pose Estimation (Q)
|
94% |
2709
3.18 IPS |
|
|
Object Detection (SP)
|
100% |
717
56.9 IPS |
|
|
Object Detection (HP)
|
100% |
717
56.9 IPS |
|
|
Object Detection (Q)
|
87% |
1192
95.6 IPS |
|
|
Face Detection (SP)
|
100% |
1843
21.9 IPS |
|
|
Face Detection (HP)
|
100% |
1842
21.9 IPS |
|
|
Face Detection (Q)
|
97% |
2923
34.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1971
15.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
1976
15.2 IPS |
|
|
Depth Estimation (Q)
|
81% |
3143
24.8 IPS |
|
|
Style Transfer (SP)
|
100% |
4448
5.72 IPS |
|
|
Style Transfer (HP)
|
100% |
4439
5.71 IPS |
|
|
Style Transfer (Q)
|
98% |
7651
9.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
900
33.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
917
33.9 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
1635
60.6 IPS |
|
|
Text Classification (SP)
|
100% |
868
1.16 KIPS |
|
|
Text Classification (HP)
|
100% |
874
1.17 KIPS |
|
|
Text Classification (Q)
|
91% |
908
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
1419
24.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1398
24.1 IPS |
|
|
Machine Translation (Q)
|
100% |
1407
24.2 IPS |
