LENOVO fud
Geekbench ML Score
5480
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 05:41 AM |
| Views | 6 |
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% |
2790
522.1 IPS |
|
|
Image Classification (F16)
|
100% |
2915
545.4 IPS |
|
|
Image Classification (I8)
|
99% |
4836
904.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
2239
37.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
2292
38.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
3396
56.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
13693
16.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
13781
16.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
46038
55.8 IPS |
|
|
Object Detection (F32)
|
100% |
2758
205.9 IPS |
|
|
Object Detection (F16)
|
100% |
2826
211.0 IPS |
|
|
Object Detection (I8)
|
62% |
2578
192.5 IPS |
|
|
Face Detection (F32)
|
100% |
5240
62.3 IPS |
|
|
Face Detection (F16)
|
100% |
5208
61.9 IPS |
|
|
Face Detection (I8)
|
89% |
5520
65.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
12128
94.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
12663
98.2 IPS |
|
|
Depth Estimation (I8)
|
96% |
21723
168.5 IPS |
|
|
Style Transfer (F32)
|
100% |
30046
39.5 IPS |
|
|
Style Transfer (F16)
|
100% |
30279
39.8 IPS |
|
|
Style Transfer (I8)
|
98% |
26211
34.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5708
203.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5721
204.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7094
253.4 IPS |
|
|
Text Classification (F32)
|
100% |
1681
2.42 KIPS |
|
|
Text Classification (F16)
|
100% |
1703
2.45 KIPS |
|
|
Text Classification (I8)
|
98% |
534
767.8 IPS |
|
|
Machine Translation (F32)
|
100% |
2645
48.7 IPS |
|
|
Machine Translation (F16)
|
100% |
2858
52.6 IPS |
|
|
Machine Translation (I8)
|
67% |
3809
70.1 IPS |
