LENOVO fud
Geekbench ML Score
5161
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 Pro (64-bit) |
| Model | LENOVO fud |
| Motherboard | LENOVO 3789 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 275HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 64.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 3.00 MB x 3 |
| L3 Cache | 36.0 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% |
2884
539.8 IPS |
|
|
Image Classification (F16)
|
100% |
2771
518.6 IPS |
|
|
Image Classification (I8)
|
99% |
4808
899.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
2232
37.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
2251
37.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
3644
60.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
13382
16.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
13198
16.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
43577
52.8 IPS |
|
|
Object Detection (F32)
|
100% |
2518
188.0 IPS |
|
|
Object Detection (F16)
|
100% |
2541
189.7 IPS |
|
|
Object Detection (I8)
|
62% |
2660
198.6 IPS |
|
|
Face Detection (F32)
|
100% |
3968
47.2 IPS |
|
|
Face Detection (F16)
|
100% |
3757
44.7 IPS |
|
|
Face Detection (I8)
|
89% |
4601
54.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
10723
83.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
11001
85.3 IPS |
|
|
Depth Estimation (I8)
|
96% |
20240
157.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29318
38.6 IPS |
|
|
Style Transfer (F16)
|
100% |
28777
37.9 IPS |
|
|
Style Transfer (I8)
|
98% |
17075
22.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5711
203.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5563
198.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
6803
243.0 IPS |
|
|
Text Classification (F32)
|
100% |
1751
2.52 KIPS |
|
|
Text Classification (F16)
|
100% |
1767
2.54 KIPS |
|
|
Text Classification (I8)
|
98% |
546
785.4 IPS |
|
|
Machine Translation (F32)
|
100% |
2862
52.7 IPS |
|
|
Machine Translation (F16)
|
100% |
2888
53.1 IPS |
|
|
Machine Translation (I8)
|
67% |
3679
67.7 IPS |
