LENOVO INVALID
Geekbench ML Score
24068
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:46 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 | 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% |
11064
2.07 KIPS |
|
|
Image Classification (F16)
|
100% |
11715
2.19 KIPS |
|
|
Image Classification (I8)
|
100% |
9796
1.83 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17314
289.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
16549
276.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
15438
257.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
174860
211.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
175447
212.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
157486
190.7 IPS |
|
|
Object Detection (F32)
|
100% |
8404
627.4 IPS |
|
|
Object Detection (F16)
|
100% |
8323
621.4 IPS |
|
|
Object Detection (I8)
|
56% |
7574
565.5 IPS |
|
|
Face Detection (F32)
|
100% |
35588
423.1 IPS |
|
|
Face Detection (F16)
|
100% |
37236
442.7 IPS |
|
|
Face Detection (I8)
|
89% |
31024
368.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
71003
550.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
67469
523.2 IPS |
|
|
Depth Estimation (I8)
|
94% |
53711
416.5 IPS |
|
|
Style Transfer (F32)
|
100% |
308354
405.6 IPS |
|
|
Style Transfer (F16)
|
100% |
312016
410.4 IPS |
|
|
Style Transfer (I8)
|
98% |
274999
361.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
44842
1.60 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
45643
1.63 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33204
1.19 KIPS |
|
|
Text Classification (F32)
|
100% |
2991
4.30 KIPS |
|
|
Text Classification (F16)
|
100% |
2987
4.29 KIPS |
|
|
Text Classification (I8)
|
98% |
1804
2.59 KIPS |
|
|
Machine Translation (F32)
|
100% |
4783
88.0 IPS |
|
|
Machine Translation (F16)
|
100% |
4793
88.2 IPS |
|
|
Machine Translation (I8)
|
70% |
2749
50.6 IPS |
