LENOVO 21QESIT004
Geekbench ML Score
2324
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 25 2025 01:38 PM |
| Views | 10 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 21QESIT004 |
| Motherboard | LENOVO 21QESIT004 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 16 |
| L1 Data Cache | 32.0 KB x 16 |
| L2 Cache | 2.00 MB x 2 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1206
225.7 IPS |
|
|
Image Classification (F16)
|
100% |
1217
227.8 IPS |
|
|
Image Classification (I8)
|
99% |
2268
424.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1070
17.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1065
17.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1632
27.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
4580
5.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
4573
5.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
14800
17.9 IPS |
|
|
Object Detection (F32)
|
100% |
1091
81.4 IPS |
|
|
Object Detection (F16)
|
100% |
1111
82.9 IPS |
|
|
Object Detection (I8)
|
62% |
1100
82.1 IPS |
|
|
Face Detection (F32)
|
100% |
2722
32.4 IPS |
|
|
Face Detection (F16)
|
100% |
2756
32.8 IPS |
|
|
Face Detection (I8)
|
89% |
3036
36.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
4234
32.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
4278
33.2 IPS |
|
|
Depth Estimation (I8)
|
96% |
7994
62.0 IPS |
|
|
Style Transfer (F32)
|
100% |
9971
13.1 IPS |
|
|
Style Transfer (F16)
|
100% |
10123
13.3 IPS |
|
|
Style Transfer (I8)
|
98% |
15008
19.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1806
64.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1762
62.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2960
105.7 IPS |
|
|
Text Classification (F32)
|
100% |
652
937.2 IPS |
|
|
Text Classification (F16)
|
100% |
658
946.2 IPS |
|
|
Text Classification (I8)
|
98% |
626
899.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1254
23.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1065
19.6 IPS |
|
|
Machine Translation (I8)
|
67% |
2259
41.6 IPS |
