LENOVO fud
Geekbench ML Score
2597
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:46 AM |
| Views | 3 |
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% |
1973
369.1 IPS |
|
|
Image Classification (F16)
|
100% |
1935
362.0 IPS |
|
|
Image Classification (I8)
|
99% |
1443
270.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1335
22.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1343
22.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1036
17.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
8464
10.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
8458
10.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
6938
8.40 IPS |
|
|
Object Detection (F32)
|
100% |
1628
121.5 IPS |
|
|
Object Detection (F16)
|
100% |
1593
118.9 IPS |
|
|
Object Detection (I8)
|
60% |
1182
88.3 IPS |
|
|
Face Detection (F32)
|
100% |
2452
29.2 IPS |
|
|
Face Detection (F16)
|
100% |
2452
29.2 IPS |
|
|
Face Detection (I8)
|
88% |
1635
19.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
6646
51.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
6456
50.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
4913
38.1 IPS |
|
|
Style Transfer (F32)
|
100% |
21193
27.9 IPS |
|
|
Style Transfer (F16)
|
100% |
21384
28.1 IPS |
|
|
Style Transfer (I8)
|
98% |
15478
20.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3997
142.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3867
138.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2554
91.2 IPS |
|
|
Text Classification (F32)
|
90% |
721
1.04 KIPS |
|
|
Text Classification (F16)
|
90% |
715
1.03 KIPS |
|
|
Text Classification (I8)
|
90% |
504
724.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1291
23.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1281
23.6 IPS |
|
|
Machine Translation (I8)
|
70% |
710
13.1 IPS |
