LENOVO 90NC00MWYS
Geekbench ML Score
2822
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 15 2024 07:22 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 90NC00MWYS |
| Motherboard | LENOVO 3717 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10700 |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 256 KB x 8 |
| L3 Cache | 16.0 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% |
1406
263.1 IPS |
|
|
Image Classification (F16)
|
100% |
1414
264.7 IPS |
|
|
Image Classification (I8)
|
97% |
2337
437.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1385
23.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1385
23.1 IPS |
|
|
Image Segmentation (I8)
|
97% |
1809
30.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
6094
7.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
5255
6.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
11341
13.7 IPS |
|
|
Object Detection (F32)
|
100% |
1643
122.6 IPS |
|
|
Object Detection (F16)
|
100% |
1626
121.4 IPS |
|
|
Object Detection (I8)
|
60% |
1499
111.9 IPS |
|
|
Face Detection (F32)
|
100% |
1861
22.1 IPS |
|
|
Face Detection (F16)
|
100% |
1910
22.7 IPS |
|
|
Face Detection (I8)
|
87% |
3211
38.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
6437
49.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
6351
49.3 IPS |
|
|
Depth Estimation (I8)
|
74% |
9616
74.6 IPS |
|
|
Style Transfer (F32)
|
100% |
14637
19.3 IPS |
|
|
Style Transfer (F16)
|
100% |
13388
17.6 IPS |
|
|
Style Transfer (I8)
|
85% |
13324
17.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2774
99.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2683
95.8 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
3077
109.9 IPS |
|
|
Text Classification (F32)
|
100% |
1459
2.10 KIPS |
|
|
Text Classification (F16)
|
100% |
1532
2.20 KIPS |
|
|
Text Classification (I8)
|
94% |
396
568.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1775
32.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1789
32.9 IPS |
|
|
Machine Translation (I8)
|
67% |
1867
34.4 IPS |
