LENOVO fud
Geekbench ML Score
3255
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:47 AM |
| Views | 4 |
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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2438
456.2 IPS |
|
|
Image Classification (F16)
|
100% |
2434
455.4 IPS |
|
|
Image Classification (I8)
|
99% |
1785
334.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1768
29.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1770
29.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1416
23.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
9066
11.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
9124
11.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
7970
9.65 IPS |
|
|
Object Detection (F32)
|
100% |
2128
158.9 IPS |
|
|
Object Detection (F16)
|
100% |
2104
157.1 IPS |
|
|
Object Detection (I8)
|
60% |
1561
116.6 IPS |
|
|
Face Detection (F32)
|
100% |
4387
52.2 IPS |
|
|
Face Detection (F16)
|
100% |
4223
50.2 IPS |
|
|
Face Detection (I8)
|
88% |
2756
32.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
7780
60.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
7807
60.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
6110
47.4 IPS |
|
|
Style Transfer (F32)
|
100% |
23822
31.3 IPS |
|
|
Style Transfer (F16)
|
100% |
24366
32.1 IPS |
|
|
Style Transfer (I8)
|
98% |
18478
24.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4699
167.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4666
166.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3001
107.2 IPS |
|
|
Text Classification (F32)
|
90% |
749
1.08 KIPS |
|
|
Text Classification (F16)
|
90% |
741
1.07 KIPS |
|
|
Text Classification (I8)
|
90% |
520
747.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1891
34.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1744
32.1 IPS |
|
|
Machine Translation (I8)
|
70% |
871
16.0 IPS |
