LENOVO fud
Geekbench ML Score
2798
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:56 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% |
2066
386.6 IPS |
|
|
Image Classification (F16)
|
100% |
2000
374.2 IPS |
|
|
Image Classification (I8)
|
99% |
1537
287.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1444
24.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1458
24.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1148
19.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8787
10.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
8833
10.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
7301
8.84 IPS |
|
|
Object Detection (F32)
|
100% |
1657
123.7 IPS |
|
|
Object Detection (F16)
|
100% |
1872
139.7 IPS |
|
|
Object Detection (I8)
|
60% |
1338
99.9 IPS |
|
|
Face Detection (F32)
|
100% |
2867
34.1 IPS |
|
|
Face Detection (F16)
|
100% |
2894
34.4 IPS |
|
|
Face Detection (I8)
|
88% |
1902
22.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
6811
52.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
6874
53.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
5237
40.6 IPS |
|
|
Style Transfer (F32)
|
100% |
22426
29.5 IPS |
|
|
Style Transfer (F16)
|
100% |
22332
29.4 IPS |
|
|
Style Transfer (I8)
|
98% |
16900
22.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4363
155.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4188
149.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2614
93.3 IPS |
|
|
Text Classification (F32)
|
90% |
746
1.07 KIPS |
|
|
Text Classification (F16)
|
90% |
739
1.06 KIPS |
|
|
Text Classification (I8)
|
90% |
520
747.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1432
26.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1454
26.8 IPS |
|
|
Machine Translation (I8)
|
70% |
756
13.9 IPS |
