LENOVO 21QESIT004
Geekbench ML Score
2652
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:38 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% |
1805
337.8 IPS |
|
|
Image Classification (F16)
|
100% |
1682
314.8 IPS |
|
|
Image Classification (I8)
|
99% |
2991
559.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1446
24.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1419
23.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
2558
42.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
6345
7.68 IPS |
|
|
Pose Estimation (F16)
|
100% |
6167
7.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
19682
23.8 IPS |
|
|
Object Detection (F32)
|
100% |
1643
122.7 IPS |
|
|
Object Detection (F16)
|
100% |
1545
115.4 IPS |
|
|
Object Detection (I8)
|
62% |
1637
122.2 IPS |
|
|
Face Detection (F32)
|
100% |
2476
29.4 IPS |
|
|
Face Detection (F16)
|
100% |
2171
25.8 IPS |
|
|
Face Detection (I8)
|
89% |
2616
31.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
4158
32.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
4417
34.3 IPS |
|
|
Depth Estimation (I8)
|
96% |
10401
80.7 IPS |
|
|
Style Transfer (F32)
|
100% |
11342
14.9 IPS |
|
|
Style Transfer (F16)
|
100% |
10010
13.2 IPS |
|
|
Style Transfer (I8)
|
98% |
11531
15.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1983
70.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2428
86.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3477
124.2 IPS |
|
|
Text Classification (F32)
|
100% |
796
1.14 KIPS |
|
|
Text Classification (F16)
|
100% |
884
1.27 KIPS |
|
|
Text Classification (I8)
|
98% |
851
1.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
783
14.4 IPS |
|
|
Machine Translation (F16)
|
100% |
869
16.0 IPS |
|
|
Machine Translation (I8)
|
67% |
1394
25.7 IPS |
