LENOVO 21QESIT004
Geekbench ML Score
2457
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:22 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1851
346.4 IPS |
|
|
Image Classification (F16)
|
100% |
1626
304.2 IPS |
|
|
Image Classification (I8)
|
99% |
1810
338.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1120
18.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1286
21.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
2270
37.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
5660
6.85 IPS |
|
|
Pose Estimation (F16)
|
100% |
2135
2.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
12074
14.6 IPS |
|
|
Object Detection (F32)
|
100% |
927
69.2 IPS |
|
|
Object Detection (F16)
|
100% |
552
41.2 IPS |
|
|
Object Detection (I8)
|
62% |
787
58.8 IPS |
|
|
Face Detection (F32)
|
100% |
1208
14.4 IPS |
|
|
Face Detection (F16)
|
100% |
1700
20.2 IPS |
|
|
Face Detection (I8)
|
89% |
2748
32.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
4253
33.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
5560
43.1 IPS |
|
|
Depth Estimation (I8)
|
96% |
9475
73.5 IPS |
|
|
Style Transfer (F32)
|
100% |
12968
17.1 IPS |
|
|
Style Transfer (F16)
|
100% |
11029
14.5 IPS |
|
|
Style Transfer (I8)
|
98% |
16548
21.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2504
89.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2829
101.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4409
157.5 IPS |
|
|
Text Classification (F32)
|
100% |
1086
1.56 KIPS |
|
|
Text Classification (F16)
|
100% |
1112
1.60 KIPS |
|
|
Text Classification (I8)
|
98% |
1064
1.53 KIPS |
|
|
Machine Translation (F32)
|
100% |
1600
29.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1002
18.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2585
47.6 IPS |
