LENOVO fud
Geekbench ML Score
5262
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 06:31 AM |
| Views | 4 |
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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2788
521.7 IPS |
|
|
Image Classification (F16)
|
100% |
2877
538.3 IPS |
|
|
Image Classification (I8)
|
99% |
4837
905.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
2275
38.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
2238
37.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
3413
57.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
13386
16.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
13542
16.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
45470
55.1 IPS |
|
|
Object Detection (F32)
|
100% |
2558
191.0 IPS |
|
|
Object Detection (F16)
|
100% |
2568
191.7 IPS |
|
|
Object Detection (I8)
|
62% |
2629
196.3 IPS |
|
|
Face Detection (F32)
|
100% |
4411
52.4 IPS |
|
|
Face Detection (F16)
|
100% |
4490
53.4 IPS |
|
|
Face Detection (I8)
|
89% |
5019
59.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
11526
89.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
11555
89.6 IPS |
|
|
Depth Estimation (I8)
|
96% |
21454
166.4 IPS |
|
|
Style Transfer (F32)
|
100% |
29419
38.7 IPS |
|
|
Style Transfer (F16)
|
100% |
29310
38.6 IPS |
|
|
Style Transfer (I8)
|
98% |
20152
26.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5809
207.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5641
201.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7462
266.5 IPS |
|
|
Text Classification (F32)
|
100% |
1679
2.41 KIPS |
|
|
Text Classification (F16)
|
100% |
1675
2.41 KIPS |
|
|
Text Classification (I8)
|
98% |
544
782.1 IPS |
|
|
Machine Translation (F32)
|
100% |
2622
48.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2566
47.2 IPS |
|
|
Machine Translation (I8)
|
67% |
3625
66.7 IPS |
