LENOVO fud
Geekbench ML Score
5369
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:53 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2830
529.5 IPS |
|
|
Image Classification (F16)
|
100% |
2815
526.8 IPS |
|
|
Image Classification (I8)
|
99% |
4878
912.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
2304
38.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2210
36.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
3503
58.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
13299
16.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
13409
16.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
44618
54.0 IPS |
|
|
Object Detection (F32)
|
100% |
2654
198.2 IPS |
|
|
Object Detection (F16)
|
100% |
2589
193.3 IPS |
|
|
Object Detection (I8)
|
62% |
2675
199.7 IPS |
|
|
Face Detection (F32)
|
100% |
4861
57.8 IPS |
|
|
Face Detection (F16)
|
100% |
4865
57.8 IPS |
|
|
Face Detection (I8)
|
89% |
5292
62.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
11542
89.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
11824
91.7 IPS |
|
|
Depth Estimation (I8)
|
96% |
21969
170.4 IPS |
|
|
Style Transfer (F32)
|
100% |
30635
40.3 IPS |
|
|
Style Transfer (F16)
|
100% |
29426
38.7 IPS |
|
|
Style Transfer (I8)
|
98% |
22734
29.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5835
208.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5806
207.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7077
252.7 IPS |
|
|
Text Classification (F32)
|
100% |
1715
2.46 KIPS |
|
|
Text Classification (F16)
|
100% |
1775
2.55 KIPS |
|
|
Text Classification (I8)
|
98% |
538
772.9 IPS |
|
|
Machine Translation (F32)
|
100% |
2718
50.0 IPS |
|
|
Machine Translation (F16)
|
100% |
2720
50.1 IPS |
|
|
Machine Translation (I8)
|
67% |
3503
64.5 IPS |
