LENOVO INVALID
Geekbench ML Score
23175
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 05:37 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% |
10899
2.04 KIPS |
|
|
Image Classification (F16)
|
100% |
11090
2.08 KIPS |
|
|
Image Classification (I8)
|
100% |
9067
1.70 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17197
287.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
16847
281.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
14641
244.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
174229
211.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
173932
210.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
155473
188.3 IPS |
|
|
Object Detection (F32)
|
100% |
7963
594.5 IPS |
|
|
Object Detection (F16)
|
100% |
8043
600.4 IPS |
|
|
Object Detection (I8)
|
56% |
7203
537.7 IPS |
|
|
Face Detection (F32)
|
100% |
34808
413.9 IPS |
|
|
Face Detection (F16)
|
100% |
34705
412.7 IPS |
|
|
Face Detection (I8)
|
89% |
29602
352.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
70212
544.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
66378
514.8 IPS |
|
|
Depth Estimation (I8)
|
94% |
53637
416.0 IPS |
|
|
Style Transfer (F32)
|
100% |
305689
402.1 IPS |
|
|
Style Transfer (F16)
|
100% |
300850
395.7 IPS |
|
|
Style Transfer (I8)
|
98% |
268517
353.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
41743
1.49 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
40130
1.43 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
32647
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
2825
4.06 KIPS |
|
|
Text Classification (F16)
|
100% |
2847
4.09 KIPS |
|
|
Text Classification (I8)
|
98% |
1790
2.57 KIPS |
|
|
Machine Translation (F32)
|
100% |
4527
83.3 IPS |
|
|
Machine Translation (F16)
|
100% |
4516
83.1 IPS |
|
|
Machine Translation (I8)
|
70% |
2489
45.8 IPS |
