[2008] SFF PC: Dell OptiPlex 160 [DC01T] Dell Inc. OptiPlex 160
Geekbench ML Score
20
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows x86 (64-bit)
Result Information
| User | inc7007 |
| Upload Date | February 15 2025 04:51 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Dell Inc. OptiPlex 160 |
| Motherboard | Dell Inc. 0H7TGR |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Atom 330 |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 28 Stepping 2 |
| Base Frequency | 1.60 GHz |
| Cluster 1 | 2 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 24.0 KB x 2 |
| L2 Cache | 512 KB x 2 |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
| Type | DDR-2 |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
10
1.87 IPS |
|
|
Image Classification (F16)
|
100% |
9
1.76 IPS |
|
|
Image Classification (I8)
|
99% |
15
2.86 IPS |
|
|
Image Segmentation (F32)
|
100% |
10
0.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
10
0.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
18
0.31 IPS |
|
|
Pose Estimation (F32)
|
100% |
17
0.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
17
0.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
35
0.04 IPS |
|
|
Object Detection (F32)
|
100% |
9
0.68 IPS |
|
|
Object Detection (F16)
|
100% |
9
0.68 IPS |
|
|
Object Detection (I8)
|
70% |
15
1.09 IPS |
|
|
Face Detection (F32)
|
100% |
30
0.35 IPS |
|
|
Face Detection (F16)
|
100% |
30
0.35 IPS |
|
|
Face Detection (I8)
|
89% |
54
0.64 IPS |
|
|
Depth Estimation (F32)
|
100% |
25
0.20 IPS |
|
|
Depth Estimation (F16)
|
100% |
25
0.20 IPS |
|
|
Depth Estimation (I8)
|
96% |
47
0.36 IPS |
|
|
Style Transfer (F32)
|
100% |
47
0.06 IPS |
|
|
Style Transfer (F16)
|
100% |
47
0.06 IPS |
|
|
Style Transfer (I8)
|
98% |
104
0.14 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12
0.43 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12
0.43 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
24
0.86 IPS |
|
|
Text Classification (F32)
|
100% |
17
24.5 IPS |
|
|
Text Classification (F16)
|
100% |
17
24.9 IPS |
|
|
Text Classification (I8)
|
98% |
16
23.1 IPS |
|
|
Machine Translation (F32)
|
100% |
22
0.40 IPS |
|
|
Machine Translation (F16)
|
100% |
22
0.40 IPS |
|
|
Machine Translation (I8)
|
67% |
24
0.44 IPS |
