HP HP ProDesk 4 SFF G1i Desktop AI PC
Geekbench AI Score
1993
Single Precision Score
9838
Half Precision Score
15194
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | January 26 2026 09:04 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | HP HP ProDesk 4 SFF G1i Desktop AI PC |
| Motherboard | HP 8D14 |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 235 |
| Topology | 1 Processor, 14 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1241
230.8 IPS |
|
|
Image Classification (HP)
|
100% |
6787
1.26 KIPS |
|
|
Image Classification (Q)
|
100% |
9708
1.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1598
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2954
47.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4001
64.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3020
3.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
35309
41.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
77044
90.2 IPS |
|
|
Object Detection (SP)
|
100% |
1110
88.0 IPS |
|
|
Object Detection (HP)
|
100% |
6396
507.4 IPS |
|
|
Object Detection (Q)
|
87% |
10299
826.6 IPS |
|
|
Face Detection (SP)
|
100% |
2911
34.6 IPS |
|
|
Face Detection (HP)
|
100% |
17586
209.0 IPS |
|
|
Face Detection (Q)
|
100% |
32825
390.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2643
20.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
18840
145.2 IPS |
|
|
Depth Estimation (Q)
|
88% |
34764
270.5 IPS |
|
|
Style Transfer (SP)
|
100% |
8934
11.5 IPS |
|
|
Style Transfer (HP)
|
100% |
52933
68.0 IPS |
|
|
Style Transfer (Q)
|
98% |
97807
126.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1097
40.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14352
530.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
22633
838.2 IPS |
|
|
Text Classification (SP)
|
100% |
1145
1.53 KIPS |
|
|
Text Classification (HP)
|
100% |
1631
2.18 KIPS |
|
|
Text Classification (Q)
|
92% |
1831
2.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1723
29.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4571
78.7 IPS |
|
|
Machine Translation (Q)
|
100% |
4600
79.2 IPS |
