LENOVO INVALID
Geekbench ML Score
23812
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:12 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 Ti SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
11196
2.10 KIPS |
|
|
Image Classification (F16)
|
100% |
11488
2.15 KIPS |
|
|
Image Classification (I8)
|
100% |
9817
1.84 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17012
284.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
16813
280.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
15441
257.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
176162
213.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
176323
213.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
157063
190.2 IPS |
|
|
Object Detection (F32)
|
100% |
8168
609.8 IPS |
|
|
Object Detection (F16)
|
100% |
8245
615.5 IPS |
|
|
Object Detection (I8)
|
56% |
7524
561.7 IPS |
|
|
Face Detection (F32)
|
100% |
36364
432.4 IPS |
|
|
Face Detection (F16)
|
100% |
36348
432.2 IPS |
|
|
Face Detection (I8)
|
89% |
29971
356.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
67304
521.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
66927
519.0 IPS |
|
|
Depth Estimation (I8)
|
94% |
54044
419.1 IPS |
|
|
Style Transfer (F32)
|
100% |
299676
394.2 IPS |
|
|
Style Transfer (F16)
|
100% |
307088
403.9 IPS |
|
|
Style Transfer (I8)
|
98% |
265909
349.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
41215
1.47 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
45154
1.61 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
31716
1.13 KIPS |
|
|
Text Classification (F32)
|
100% |
3000
4.31 KIPS |
|
|
Text Classification (F16)
|
100% |
3012
4.33 KIPS |
|
|
Text Classification (I8)
|
98% |
1791
2.57 KIPS |
|
|
Machine Translation (F32)
|
100% |
4825
88.8 IPS |
|
|
Machine Translation (F16)
|
100% |
4855
89.3 IPS |
|
|
Machine Translation (I8)
|
70% |
2767
50.9 IPS |
