LENOVO 90K800CWIN
Geekbench ML Score
904
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | December 24 2024 10:12 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | LENOVO 90K800CWIN |
| Motherboard | LENOVO 3140 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i3-8100 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 11 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 6.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 20.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
432
80.9 IPS |
|
|
Image Classification (F16)
|
100% |
370
69.2 IPS |
|
|
Image Classification (I8)
|
97% |
679
127.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
338
5.64 IPS |
|
|
Image Segmentation (F16)
|
100% |
318
5.31 IPS |
|
|
Image Segmentation (I8)
|
97% |
806
13.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1533
1.86 IPS |
|
|
Pose Estimation (F16)
|
100% |
1592
1.93 IPS |
|
|
Pose Estimation (I8)
|
100% |
3419
4.14 IPS |
|
|
Object Detection (F32)
|
100% |
424
31.7 IPS |
|
|
Object Detection (F16)
|
100% |
456
34.0 IPS |
|
|
Object Detection (I8)
|
60% |
527
39.4 IPS |
|
|
Face Detection (F32)
|
100% |
546
6.49 IPS |
|
|
Face Detection (F16)
|
100% |
560
6.66 IPS |
|
|
Face Detection (I8)
|
87% |
995
11.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1497
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
1528
11.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
2831
22.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3479
4.58 IPS |
|
|
Style Transfer (F16)
|
100% |
3554
4.68 IPS |
|
|
Style Transfer (I8)
|
85% |
4339
5.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
843
30.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
883
31.5 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1163
41.5 IPS |
|
|
Text Classification (F32)
|
100% |
680
977.0 IPS |
|
|
Text Classification (F16)
|
100% |
668
959.8 IPS |
|
|
Text Classification (I8)
|
94% |
517
742.4 IPS |
|
|
Machine Translation (F32)
|
100% |
623
11.5 IPS |
|
|
Machine Translation (F16)
|
100% |
631
11.6 IPS |
|
|
Machine Translation (I8)
|
67% |
732
13.5 IPS |
