LENOVO INVALID
Geekbench ML Score
23208
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 05:34 AM |
| Views | 4 |
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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 Ti SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
10640
1.99 KIPS |
|
|
Image Classification (F16)
|
100% |
11181
2.09 KIPS |
|
|
Image Classification (I8)
|
100% |
9434
1.77 KIPS |
|
|
Image Segmentation (F32)
|
100% |
16773
280.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
15394
257.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
15134
252.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
174424
211.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
174464
211.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
156715
189.8 IPS |
|
|
Object Detection (F32)
|
100% |
7970
595.0 IPS |
|
|
Object Detection (F16)
|
100% |
7987
596.3 IPS |
|
|
Object Detection (I8)
|
56% |
7318
546.3 IPS |
|
|
Face Detection (F32)
|
100% |
33743
401.2 IPS |
|
|
Face Detection (F16)
|
100% |
34400
409.0 IPS |
|
|
Face Detection (I8)
|
89% |
28901
343.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
68930
534.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
66279
514.0 IPS |
|
|
Depth Estimation (I8)
|
94% |
53470
414.7 IPS |
|
|
Style Transfer (F32)
|
100% |
305861
402.3 IPS |
|
|
Style Transfer (F16)
|
100% |
304574
400.6 IPS |
|
|
Style Transfer (I8)
|
98% |
261993
344.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
43297
1.55 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
39274
1.40 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
32803
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
3024
4.35 KIPS |
|
|
Text Classification (F16)
|
100% |
2911
4.18 KIPS |
|
|
Text Classification (I8)
|
98% |
1826
2.62 KIPS |
|
|
Machine Translation (F32)
|
100% |
4548
83.7 IPS |
|
|
Machine Translation (F16)
|
100% |
4636
85.3 IPS |
|
|
Machine Translation (I8)
|
70% |
2531
46.6 IPS |
