LENOVO fud
Geekbench ML Score
5389
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:54 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2790
522.2 IPS |
|
|
Image Classification (F16)
|
100% |
2783
520.9 IPS |
|
|
Image Classification (I8)
|
99% |
4817
901.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
2343
39.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
2239
37.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
3574
59.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
13219
16.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
13629
16.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
45078
54.6 IPS |
|
|
Object Detection (F32)
|
100% |
2538
189.5 IPS |
|
|
Object Detection (F16)
|
100% |
2600
194.1 IPS |
|
|
Object Detection (I8)
|
62% |
2725
203.4 IPS |
|
|
Face Detection (F32)
|
100% |
4867
57.9 IPS |
|
|
Face Detection (F16)
|
100% |
4874
58.0 IPS |
|
|
Face Detection (I8)
|
89% |
5286
62.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
11767
91.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
11580
89.8 IPS |
|
|
Depth Estimation (I8)
|
96% |
22083
171.3 IPS |
|
|
Style Transfer (F32)
|
100% |
30113
39.6 IPS |
|
|
Style Transfer (F16)
|
100% |
30013
39.5 IPS |
|
|
Style Transfer (I8)
|
98% |
22094
29.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5683
203.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5775
206.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7277
259.9 IPS |
|
|
Text Classification (F32)
|
100% |
1761
2.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1784
2.56 KIPS |
|
|
Text Classification (I8)
|
98% |
544
781.1 IPS |
|
|
Machine Translation (F32)
|
100% |
2736
50.4 IPS |
|
|
Machine Translation (F16)
|
100% |
2756
50.7 IPS |
|
|
Machine Translation (I8)
|
67% |
3713
68.3 IPS |
