HP HP Elite Mini 800 G9 Desktop PC
Geekbench ML Score
1283
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 18 2024 12:14 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | HP HP Elite Mini 800 G9 Desktop PC |
| Motherboard | HP 8AC3 |
| Power Plan | HP Optimized (Modern Standby) |
| CPU Information | |
|---|---|
| Name | Intel Core i5-14500 |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 191 Stepping 2 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics 770 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
624
116.8 IPS |
|
|
Image Classification (F16)
|
100% |
631
118.0 IPS |
|
|
Image Classification (I8)
|
100% |
499
93.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
905
15.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
923
15.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
712
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
3786
4.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
3834
4.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
2799
3.39 IPS |
|
|
Object Detection (F32)
|
100% |
683
51.0 IPS |
|
|
Object Detection (F16)
|
100% |
636
47.5 IPS |
|
|
Object Detection (I8)
|
54% |
553
41.3 IPS |
|
|
Face Detection (F32)
|
100% |
1353
16.1 IPS |
|
|
Face Detection (F16)
|
100% |
1346
16.0 IPS |
|
|
Face Detection (I8)
|
89% |
956
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
2845
22.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2838
22.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2180
16.9 IPS |
|
|
Style Transfer (F32)
|
100% |
10282
13.5 IPS |
|
|
Style Transfer (F16)
|
100% |
10266
13.5 IPS |
|
|
Style Transfer (I8)
|
98% |
7578
9.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1658
59.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1667
59.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
923
33.0 IPS |
|
|
Text Classification (F32)
|
100% |
690
992.1 IPS |
|
|
Text Classification (F16)
|
100% |
691
993.5 IPS |
|
|
Text Classification (I8)
|
98% |
372
534.9 IPS |
|
|
Machine Translation (F32)
|
100% |
610
11.2 IPS |
|
|
Machine Translation (F16)
|
100% |
610
11.2 IPS |
|
|
Machine Translation (I8)
|
70% |
380
6.99 IPS |
