HP HP EliteDesk 800 G4 DM 35W (TAA)
Geekbench ML Score
1523
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | saiht |
| Upload Date | July 25 2024 01:38 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | HP HP EliteDesk 800 G4 DM 35W (TAA) |
| Motherboard | HP 83E2 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-8500T |
| Topology | 1 Processor, 6 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 10 |
| Base Frequency | 2.11 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 3 |
| L1 Data Cache | 32.0 KB x 3 |
| L2 Cache | 256 KB x 3 |
| L3 Cache | 9.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
782
146.4 IPS |
|
|
Image Classification (F16)
|
100% |
825
154.5 IPS |
|
|
Image Classification (I8)
|
97% |
1252
234.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
723
12.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
658
11.0 IPS |
|
|
Image Segmentation (I8)
|
97% |
984
16.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
3049
3.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
2990
3.62 IPS |
|
|
Pose Estimation (I8)
|
100% |
4771
5.78 IPS |
|
|
Object Detection (F32)
|
100% |
753
56.2 IPS |
|
|
Object Detection (F16)
|
100% |
842
62.8 IPS |
|
|
Object Detection (I8)
|
60% |
815
60.9 IPS |
|
|
Face Detection (F32)
|
100% |
1398
16.6 IPS |
|
|
Face Detection (F16)
|
100% |
1421
16.9 IPS |
|
|
Face Detection (I8)
|
87% |
1976
23.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2761
21.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
3030
23.5 IPS |
|
|
Depth Estimation (I8)
|
74% |
4666
36.2 IPS |
|
|
Style Transfer (F32)
|
100% |
6778
8.92 IPS |
|
|
Style Transfer (F16)
|
100% |
6287
8.27 IPS |
|
|
Style Transfer (I8)
|
85% |
8168
10.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1407
50.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1361
48.6 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1690
60.3 IPS |
|
|
Text Classification (F32)
|
100% |
802
1.15 KIPS |
|
|
Text Classification (F16)
|
100% |
800
1.15 KIPS |
|
|
Text Classification (I8)
|
94% |
226
325.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1087
20.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1078
19.8 IPS |
|
|
Machine Translation (I8)
|
67% |
1218
22.4 IPS |
