LENOVO INVALID
Geekbench ML Score
3016
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | April 23 2025 12:29 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO INVALID |
| Motherboard | LENOVO 337B |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 235 |
| Topology | 1 Processor, 14 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 64.0 KB x 7 |
| L1 Data Cache | 48.0 KB x 7 |
| L2 Cache | 3.00 MB x 1 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1916
358.5 IPS |
|
|
Image Classification (F16)
|
100% |
1934
362.0 IPS |
|
|
Image Classification (I8)
|
100% |
1434
268.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
2365
39.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2358
39.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1698
28.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
7590
9.19 IPS |
|
|
Pose Estimation (F16)
|
100% |
7560
9.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
6646
8.05 IPS |
|
|
Object Detection (F32)
|
100% |
1879
140.3 IPS |
|
|
Object Detection (F16)
|
100% |
1877
140.1 IPS |
|
|
Object Detection (I8)
|
55% |
1442
107.6 IPS |
|
|
Face Detection (F32)
|
100% |
3565
42.4 IPS |
|
|
Face Detection (F16)
|
100% |
3802
45.2 IPS |
|
|
Face Detection (I8)
|
89% |
2481
29.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
6880
53.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
6971
54.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
5344
41.4 IPS |
|
|
Style Transfer (F32)
|
100% |
19138
25.2 IPS |
|
|
Style Transfer (F16)
|
100% |
19410
25.5 IPS |
|
|
Style Transfer (I8)
|
98% |
15611
20.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4049
144.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4053
144.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2736
97.7 IPS |
|
|
Text Classification (F32)
|
100% |
857
1.23 KIPS |
|
|
Text Classification (F16)
|
100% |
808
1.16 KIPS |
|
|
Text Classification (I8)
|
98% |
494
710.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1919
35.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1891
34.8 IPS |
|
|
Machine Translation (I8)
|
70% |
889
16.4 IPS |
