LENOVO 21QESIT004
Geekbench ML Score
2699
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:55 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | LENOVO 21QESIT004 |
| Motherboard | LENOVO 21QESIT004 |
| 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 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 3.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1829
342.2 IPS |
|
|
Image Classification (F16)
|
100% |
1574
294.5 IPS |
|
|
Image Classification (I8)
|
99% |
1804
337.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
961
16.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1111
18.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
2326
38.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
5647
6.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
3410
4.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
16896
20.5 IPS |
|
|
Object Detection (F32)
|
100% |
1404
104.8 IPS |
|
|
Object Detection (F16)
|
100% |
1346
100.5 IPS |
|
|
Object Detection (I8)
|
62% |
1414
105.6 IPS |
|
|
Face Detection (F32)
|
100% |
2174
25.8 IPS |
|
|
Face Detection (F16)
|
100% |
1636
19.5 IPS |
|
|
Face Detection (I8)
|
89% |
2339
27.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
5159
40.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
4906
38.0 IPS |
|
|
Depth Estimation (I8)
|
96% |
10923
84.7 IPS |
|
|
Style Transfer (F32)
|
100% |
12726
16.7 IPS |
|
|
Style Transfer (F16)
|
100% |
10844
14.3 IPS |
|
|
Style Transfer (I8)
|
98% |
12856
16.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2511
89.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2797
99.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4805
171.6 IPS |
|
|
Text Classification (F32)
|
100% |
1124
1.62 KIPS |
|
|
Text Classification (F16)
|
100% |
1080
1.55 KIPS |
|
|
Text Classification (I8)
|
98% |
1067
1.53 KIPS |
|
|
Machine Translation (F32)
|
100% |
1584
29.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1118
20.6 IPS |
|
|
Machine Translation (I8)
|
67% |
2461
45.3 IPS |
