LENOVO INVALID
Geekbench ML Score
23968
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 06:31 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO INVALID |
| Motherboard | LENOVO 3784 |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265K |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| L1 Instruction Cache | 64.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 3.00 MB x 2 |
| L3 Cache | 30.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 Ti SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
11586
2.17 KIPS |
|
|
Image Classification (F16)
|
100% |
11738
2.20 KIPS |
|
|
Image Classification (I8)
|
100% |
9837
1.84 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17088
285.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
16734
279.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
15272
255.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
176038
213.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
175809
212.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
157324
190.5 IPS |
|
|
Object Detection (F32)
|
100% |
8347
623.2 IPS |
|
|
Object Detection (F16)
|
100% |
8025
599.1 IPS |
|
|
Object Detection (I8)
|
56% |
7688
574.0 IPS |
|
|
Face Detection (F32)
|
100% |
36132
429.6 IPS |
|
|
Face Detection (F16)
|
100% |
37283
443.3 IPS |
|
|
Face Detection (I8)
|
89% |
30927
367.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
70978
550.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
67875
526.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
53823
417.4 IPS |
|
|
Style Transfer (F32)
|
100% |
310373
408.3 IPS |
|
|
Style Transfer (F16)
|
100% |
312581
411.2 IPS |
|
|
Style Transfer (I8)
|
98% |
272310
358.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
41989
1.50 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
39756
1.42 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33211
1.19 KIPS |
|
|
Text Classification (F32)
|
100% |
3000
4.31 KIPS |
|
|
Text Classification (F16)
|
100% |
3005
4.32 KIPS |
|
|
Text Classification (I8)
|
98% |
1828
2.63 KIPS |
|
|
Machine Translation (F32)
|
100% |
4842
89.1 IPS |
|
|
Machine Translation (F16)
|
100% |
4827
88.8 IPS |
|
|
Machine Translation (I8)
|
70% |
2744
50.5 IPS |
