LENOVO INVALID
Geekbench ML Score
23863
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:48 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 | 128.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 Ti SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
11318
2.12 KIPS |
|
|
Image Classification (F16)
|
100% |
11350
2.12 KIPS |
|
|
Image Classification (I8)
|
100% |
9833
1.84 KIPS |
|
|
Image Segmentation (F32)
|
100% |
16812
280.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
16685
278.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
15386
257.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
175783
212.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
174675
211.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
157814
191.1 IPS |
|
|
Object Detection (F32)
|
100% |
8339
622.5 IPS |
|
|
Object Detection (F16)
|
100% |
8094
604.3 IPS |
|
|
Object Detection (I8)
|
56% |
7643
570.6 IPS |
|
|
Face Detection (F32)
|
100% |
36077
429.0 IPS |
|
|
Face Detection (F16)
|
100% |
35888
426.7 IPS |
|
|
Face Detection (I8)
|
89% |
30105
358.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
69134
536.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
68013
527.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
54018
418.9 IPS |
|
|
Style Transfer (F32)
|
100% |
308688
406.1 IPS |
|
|
Style Transfer (F16)
|
100% |
316559
416.4 IPS |
|
|
Style Transfer (I8)
|
98% |
268321
353.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
44298
1.58 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
41749
1.49 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33178
1.18 KIPS |
|
|
Text Classification (F32)
|
100% |
2984
4.29 KIPS |
|
|
Text Classification (F16)
|
100% |
2968
4.27 KIPS |
|
|
Text Classification (I8)
|
98% |
1782
2.56 KIPS |
|
|
Machine Translation (F32)
|
100% |
4807
88.5 IPS |
|
|
Machine Translation (F16)
|
100% |
4774
87.9 IPS |
|
|
Machine Translation (I8)
|
70% |
2732
50.3 IPS |
