LENOVO fud
Geekbench ML Score
3220
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:13 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 | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2332
436.3 IPS |
|
|
Image Classification (F16)
|
100% |
2396
448.4 IPS |
|
|
Image Classification (I8)
|
99% |
1749
327.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1763
29.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1770
29.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1388
23.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
9114
11.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
9096
11.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
7912
9.58 IPS |
|
|
Object Detection (F32)
|
100% |
2024
151.1 IPS |
|
|
Object Detection (F16)
|
100% |
2009
150.0 IPS |
|
|
Object Detection (I8)
|
60% |
1520
113.5 IPS |
|
|
Face Detection (F32)
|
100% |
4304
51.2 IPS |
|
|
Face Detection (F16)
|
100% |
4219
50.2 IPS |
|
|
Face Detection (I8)
|
88% |
2791
33.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
7825
60.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
7812
60.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
5991
46.5 IPS |
|
|
Style Transfer (F32)
|
100% |
23579
31.0 IPS |
|
|
Style Transfer (F16)
|
100% |
23637
31.1 IPS |
|
|
Style Transfer (I8)
|
98% |
18580
24.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4681
167.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4485
160.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3053
109.0 IPS |
|
|
Text Classification (F32)
|
90% |
753
1.08 KIPS |
|
|
Text Classification (F16)
|
90% |
741
1.07 KIPS |
|
|
Text Classification (I8)
|
90% |
519
745.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1804
33.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1789
32.9 IPS |
|
|
Machine Translation (I8)
|
70% |
873
16.1 IPS |
