HP HP Z2 Tower G9 Workstation Desktop PC
Geekbench AI Score
14644
Single Precision Score
25691
Half Precision Score
11430
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | rolandrasch |
| Upload Date | January 23 2025 12:38 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX 2000 Ada Generation |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | HP HP Z2 Tower G9 Workstation Desktop PC |
| Motherboard | HP 895C |
| Power Plan | HP Optimized (empfohlen) |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900K |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6102
1.13 KIPS |
|
|
Image Classification (HP)
|
99% |
11775
2.20 KIPS |
|
|
Image Classification (Q)
|
99% |
5634
1.05 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9575
155.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
13115
212.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
8824
143.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
65717
76.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
199866
233.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
58680
68.8 IPS |
|
|
Object Detection (SP)
|
100% |
7408
587.6 IPS |
|
|
Object Detection (HP)
|
100% |
13373
1.06 KIPS |
|
|
Object Detection (Q)
|
84% |
6414
517.3 IPS |
|
|
Face Detection (SP)
|
100% |
17284
205.4 IPS |
|
|
Face Detection (HP)
|
100% |
28374
337.2 IPS |
|
|
Face Detection (Q)
|
97% |
14901
177.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
31651
243.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
66051
508.9 IPS |
|
|
Depth Estimation (Q)
|
77% |
26796
214.8 IPS |
|
|
Style Transfer (SP)
|
100% |
115781
148.8 IPS |
|
|
Style Transfer (HP)
|
100% |
306147
393.6 IPS |
|
|
Style Transfer (Q)
|
98% |
103457
133.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
24682
911.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
41301
1.53 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
17702
655.5 IPS |
|
|
Text Classification (SP)
|
100% |
3221
4.30 KIPS |
|
|
Text Classification (HP)
|
99% |
3855
5.14 KIPS |
|
|
Text Classification (Q)
|
97% |
1904
2.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
3168
54.6 IPS |
|
|
Machine Translation (HP)
|
100% |
3322
57.2 IPS |
|
|
Machine Translation (Q)
|
70% |
1462
27.4 IPS |
