LENOVO INVALID
Geekbench ML Score
23900
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 06:33 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% |
11383
2.13 KIPS |
|
|
Image Classification (F16)
|
100% |
11599
2.17 KIPS |
|
|
Image Classification (I8)
|
100% |
9985
1.87 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17351
289.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
16536
276.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
14849
248.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
176015
213.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
176015
213.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
157276
190.5 IPS |
|
|
Object Detection (F32)
|
100% |
8318
621.0 IPS |
|
|
Object Detection (F16)
|
100% |
8299
619.5 IPS |
|
|
Object Detection (I8)
|
56% |
7702
575.0 IPS |
|
|
Face Detection (F32)
|
100% |
35969
427.7 IPS |
|
|
Face Detection (F16)
|
100% |
36052
428.7 IPS |
|
|
Face Detection (I8)
|
89% |
30157
358.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
70020
543.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
67545
523.8 IPS |
|
|
Depth Estimation (I8)
|
94% |
54444
422.2 IPS |
|
|
Style Transfer (F32)
|
100% |
312662
411.3 IPS |
|
|
Style Transfer (F16)
|
100% |
306919
403.7 IPS |
|
|
Style Transfer (I8)
|
98% |
274761
361.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
39828
1.42 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
44364
1.58 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33195
1.19 KIPS |
|
|
Text Classification (F32)
|
100% |
2990
4.30 KIPS |
|
|
Text Classification (F16)
|
100% |
2835
4.07 KIPS |
|
|
Text Classification (I8)
|
98% |
1828
2.63 KIPS |
|
|
Machine Translation (F32)
|
100% |
4838
89.0 IPS |
|
|
Machine Translation (F16)
|
100% |
4810
88.5 IPS |
|
|
Machine Translation (I8)
|
70% |
2754
50.7 IPS |
