LENOVO fud
Geekbench ML Score
2596
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:42 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1993
372.9 IPS |
|
|
Image Classification (F16)
|
100% |
1948
364.5 IPS |
|
|
Image Classification (I8)
|
99% |
1423
266.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1316
22.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1323
22.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1028
17.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8352
10.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
8306
10.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
6994
8.47 IPS |
|
|
Object Detection (F32)
|
100% |
1709
127.6 IPS |
|
|
Object Detection (F16)
|
100% |
1357
101.3 IPS |
|
|
Object Detection (I8)
|
60% |
1231
91.9 IPS |
|
|
Face Detection (F32)
|
100% |
2432
28.9 IPS |
|
|
Face Detection (F16)
|
100% |
2452
29.1 IPS |
|
|
Face Detection (I8)
|
88% |
1612
19.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
6460
50.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
6276
48.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
4856
37.7 IPS |
|
|
Style Transfer (F32)
|
100% |
21293
28.0 IPS |
|
|
Style Transfer (F16)
|
100% |
21741
28.6 IPS |
|
|
Style Transfer (I8)
|
98% |
15915
20.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4006
143.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4008
143.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2485
88.8 IPS |
|
|
Text Classification (F32)
|
90% |
725
1.04 KIPS |
|
|
Text Classification (F16)
|
90% |
712
1.02 KIPS |
|
|
Text Classification (I8)
|
90% |
503
723.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1454
26.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1311
24.1 IPS |
|
|
Machine Translation (I8)
|
70% |
718
13.2 IPS |
