HP HP ProDesk 600 G2 SFF
Geekbench AI Score
2202
Single Precision Score
2194
Half Precision Score
3162
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | jchillari |
| Upload Date | December 13 2025 11:18 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows Server 2019 Standard (64-bit) |
| Model | HP HP ProDesk 600 G2 SFF |
| Motherboard | HP 805D |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-6700 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 3.41 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1308
243.2 IPS |
|
|
Image Classification (HP)
|
100% |
1302
242.2 IPS |
|
|
Image Classification (Q)
|
100% |
2079
386.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1374
22.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1371
22.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
2338
38.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2688
3.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
2696
3.15 IPS |
|
|
Pose Estimation (Q)
|
94% |
4968
5.83 IPS |
|
|
Object Detection (SP)
|
100% |
1299
103.0 IPS |
|
|
Object Detection (HP)
|
100% |
1306
103.6 IPS |
|
|
Object Detection (Q)
|
87% |
2084
167.1 IPS |
|
|
Face Detection (SP)
|
100% |
2610
31.0 IPS |
|
|
Face Detection (HP)
|
100% |
2536
30.1 IPS |
|
|
Face Detection (Q)
|
97% |
5322
63.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
3480
26.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3496
26.9 IPS |
|
|
Depth Estimation (Q)
|
81% |
5524
43.6 IPS |
|
|
Style Transfer (SP)
|
100% |
7769
9.99 IPS |
|
|
Style Transfer (HP)
|
100% |
7777
10.00 IPS |
|
|
Style Transfer (Q)
|
98% |
14031
18.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1594
58.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1593
58.8 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
2915
108.0 IPS |
|
|
Text Classification (SP)
|
100% |
1641
2.19 KIPS |
|
|
Text Classification (HP)
|
100% |
1644
2.19 KIPS |
|
|
Text Classification (Q)
|
91% |
716
962.2 IPS |
|
|
Machine Translation (SP)
|
100% |
2319
39.9 IPS |
|
|
Machine Translation (HP)
|
100% |
2279
39.2 IPS |
|
|
Machine Translation (Q)
|
100% |
2313
39.9 IPS |
