LENOVO fud
Geekbench ML Score
5448
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 05:43 AM |
| Views | 8 |
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% |
2776
519.4 IPS |
|
|
Image Classification (F16)
|
100% |
2664
498.5 IPS |
|
|
Image Classification (I8)
|
99% |
4697
878.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
2229
37.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2364
39.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
3502
58.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
13368
16.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
13283
16.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
45706
55.3 IPS |
|
|
Object Detection (F32)
|
100% |
2657
198.3 IPS |
|
|
Object Detection (F16)
|
100% |
2709
202.2 IPS |
|
|
Object Detection (I8)
|
62% |
2648
197.7 IPS |
|
|
Face Detection (F32)
|
100% |
5302
63.0 IPS |
|
|
Face Detection (F16)
|
100% |
5266
62.6 IPS |
|
|
Face Detection (I8)
|
89% |
5557
66.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12338
95.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
12690
98.4 IPS |
|
|
Depth Estimation (I8)
|
96% |
21327
165.4 IPS |
|
|
Style Transfer (F32)
|
100% |
29278
38.5 IPS |
|
|
Style Transfer (F16)
|
100% |
30072
39.6 IPS |
|
|
Style Transfer (I8)
|
98% |
26368
34.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5622
200.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5712
204.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7252
259.0 IPS |
|
|
Text Classification (F32)
|
100% |
1823
2.62 KIPS |
|
|
Text Classification (F16)
|
100% |
1743
2.50 KIPS |
|
|
Text Classification (I8)
|
98% |
543
780.9 IPS |
|
|
Machine Translation (F32)
|
100% |
2841
52.3 IPS |
|
|
Machine Translation (F16)
|
100% |
2534
46.6 IPS |
|
|
Machine Translation (I8)
|
67% |
3557
65.5 IPS |
