LENOVO fud
Geekbench ML Score
3265
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:51 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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2376
444.7 IPS |
|
|
Image Classification (F16)
|
100% |
2409
450.8 IPS |
|
|
Image Classification (I8)
|
99% |
1796
336.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1767
29.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1754
29.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1409
23.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
9175
11.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
9105
11.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
7997
9.68 IPS |
|
|
Object Detection (F32)
|
100% |
2037
152.1 IPS |
|
|
Object Detection (F16)
|
100% |
2039
152.2 IPS |
|
|
Object Detection (I8)
|
60% |
1621
121.0 IPS |
|
|
Face Detection (F32)
|
100% |
4418
52.5 IPS |
|
|
Face Detection (F16)
|
100% |
4252
50.6 IPS |
|
|
Face Detection (I8)
|
88% |
2846
33.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
7867
61.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
7950
61.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
6116
47.4 IPS |
|
|
Style Transfer (F32)
|
100% |
23455
30.9 IPS |
|
|
Style Transfer (F16)
|
100% |
23440
30.8 IPS |
|
|
Style Transfer (I8)
|
98% |
18818
24.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4702
167.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4667
166.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3242
115.8 IPS |
|
|
Text Classification (F32)
|
90% |
748
1.08 KIPS |
|
|
Text Classification (F16)
|
90% |
750
1.08 KIPS |
|
|
Text Classification (I8)
|
90% |
518
745.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1816
33.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1844
33.9 IPS |
|
|
Machine Translation (I8)
|
70% |
886
16.3 IPS |
