LENOVO fud
Geekbench ML Score
2823
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:59 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 24 |
| L1 Data Cache | 32.0 KB x 24 |
| L2 Cache | 4.00 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% |
2082
389.6 IPS |
|
|
Image Classification (F16)
|
100% |
2128
398.3 IPS |
|
|
Image Classification (I8)
|
99% |
1543
288.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1495
25.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1455
24.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1148
19.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8822
10.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
8741
10.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
7284
8.82 IPS |
|
|
Object Detection (F32)
|
100% |
1669
124.6 IPS |
|
|
Object Detection (F16)
|
100% |
1743
130.1 IPS |
|
|
Object Detection (I8)
|
60% |
1400
104.5 IPS |
|
|
Face Detection (F32)
|
100% |
2842
33.8 IPS |
|
|
Face Detection (F16)
|
100% |
2896
34.4 IPS |
|
|
Face Detection (I8)
|
88% |
1802
21.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
7145
55.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
7015
54.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
5191
40.3 IPS |
|
|
Style Transfer (F32)
|
100% |
21832
28.7 IPS |
|
|
Style Transfer (F16)
|
100% |
22309
29.3 IPS |
|
|
Style Transfer (I8)
|
98% |
16651
21.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4361
155.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4081
145.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2807
100.2 IPS |
|
|
Text Classification (F32)
|
90% |
688
988.2 IPS |
|
|
Text Classification (F16)
|
90% |
728
1.05 KIPS |
|
|
Text Classification (I8)
|
90% |
515
740.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1661
30.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1582
29.1 IPS |
|
|
Machine Translation (I8)
|
70% |
808
14.9 IPS |
