LENOVO fud
Geekbench ML Score
2741
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 06:33 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2046
382.9 IPS |
|
|
Image Classification (F16)
|
100% |
1992
372.7 IPS |
|
|
Image Classification (I8)
|
99% |
1514
283.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1454
24.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1408
23.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1117
18.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
8688
10.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
8701
10.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
7216
8.74 IPS |
|
|
Object Detection (F32)
|
100% |
1580
118.0 IPS |
|
|
Object Detection (F16)
|
100% |
1639
122.4 IPS |
|
|
Object Detection (I8)
|
60% |
1303
97.3 IPS |
|
|
Face Detection (F32)
|
100% |
2760
32.8 IPS |
|
|
Face Detection (F16)
|
100% |
2744
32.6 IPS |
|
|
Face Detection (I8)
|
88% |
1814
21.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
6909
53.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
6975
54.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
5067
39.3 IPS |
|
|
Style Transfer (F32)
|
100% |
22082
29.0 IPS |
|
|
Style Transfer (F16)
|
100% |
22080
29.0 IPS |
|
|
Style Transfer (I8)
|
98% |
16407
21.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4306
153.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4226
150.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2721
97.2 IPS |
|
|
Text Classification (F32)
|
90% |
751
1.08 KIPS |
|
|
Text Classification (F16)
|
90% |
727
1.05 KIPS |
|
|
Text Classification (I8)
|
90% |
512
736.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1384
25.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1378
25.4 IPS |
|
|
Machine Translation (I8)
|
70% |
746
13.7 IPS |
