LENOVO 21QESIT004
Geekbench ML Score
1448
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:43 AM |
| Views | 3 |
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% |
1154
215.9 IPS |
|
|
Image Classification (F16)
|
100% |
605
113.2 IPS |
|
|
Image Classification (I8)
|
99% |
1247
233.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
600
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
694
11.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1678
28.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
2241
2.71 IPS |
|
|
Pose Estimation (F16)
|
100% |
1767
2.14 IPS |
|
|
Pose Estimation (I8)
|
100% |
7932
9.61 IPS |
|
|
Object Detection (F32)
|
100% |
1213
90.5 IPS |
|
|
Object Detection (F16)
|
100% |
535
39.9 IPS |
|
|
Object Detection (I8)
|
62% |
905
67.6 IPS |
|
|
Face Detection (F32)
|
100% |
939
11.2 IPS |
|
|
Face Detection (F16)
|
100% |
704
8.37 IPS |
|
|
Face Detection (I8)
|
89% |
1537
18.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1881
14.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
1573
12.2 IPS |
|
|
Depth Estimation (I8)
|
96% |
6364
49.4 IPS |
|
|
Style Transfer (F32)
|
100% |
4963
6.53 IPS |
|
|
Style Transfer (F16)
|
100% |
4159
5.47 IPS |
|
|
Style Transfer (I8)
|
98% |
7753
10.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1085
38.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1284
45.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2989
106.8 IPS |
|
|
Text Classification (F32)
|
100% |
770
1.11 KIPS |
|
|
Text Classification (F16)
|
100% |
790
1.14 KIPS |
|
|
Text Classification (I8)
|
98% |
873
1.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
947
17.4 IPS |
|
|
Machine Translation (F16)
|
100% |
557
10.3 IPS |
|
|
Machine Translation (I8)
|
67% |
1688
31.1 IPS |
