HP HP ProDesk 400 G3 MT
Geekbench AI Score
1419
Single Precision Score
2092
Half Precision Score
1980
Quantized Score
Geekbench AI 1.3.0 for Linux AVX2
Result Information
| User | akostadinov |
| Upload Date | April 11 2025 07:47 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) HD Graphics 530 (iGPU) |
| System Information | |
|---|---|
| Operating System | Fedora Linux 40 (Forty) |
| Model | HP HP ProDesk 400 G3 MT |
| Motherboard | HP 8061 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-6500 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
949
176.5 IPS |
|
|
Image Classification (HP)
|
100% |
1408
261.9 IPS |
|
|
Image Classification (Q)
|
100% |
1264
235.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1172
19.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2185
35.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
2042
33.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2319
2.71 IPS |
|
|
Pose Estimation (HP)
|
99% |
2158
2.53 IPS |
|
|
Pose Estimation (Q)
|
97% |
3194
3.74 IPS |
|
|
Object Detection (SP)
|
100% |
877
69.6 IPS |
|
|
Object Detection (HP)
|
99% |
1389
110.5 IPS |
|
|
Object Detection (Q)
|
88% |
1302
104.5 IPS |
|
|
Face Detection (SP)
|
100% |
2395
28.5 IPS |
|
|
Face Detection (HP)
|
100% |
4038
48.0 IPS |
|
|
Face Detection (Q)
|
97% |
3696
44.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2794
21.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
4491
34.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
4051
31.5 IPS |
|
|
Style Transfer (SP)
|
100% |
5767
7.41 IPS |
|
|
Style Transfer (HP)
|
100% |
8469
10.9 IPS |
|
|
Style Transfer (Q)
|
98% |
7521
9.70 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1204
44.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1886
69.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1798
66.6 IPS |
|
|
Text Classification (SP)
|
71% |
444
641.9 IPS |
|
|
Text Classification (HP)
|
71% |
621
898.8 IPS |
|
|
Text Classification (Q)
|
92% |
442
594.1 IPS |
|
|
Machine Translation (SP)
|
100% |
713
12.3 IPS |
|
|
Machine Translation (HP)
|
97% |
972
16.8 IPS |
|
|
Machine Translation (Q)
|
98% |
967
16.7 IPS |
