LENOVO INVALID
Geekbench ML Score
24214
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:06 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 | 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% |
11300
2.11 KIPS |
|
|
Image Classification (F16)
|
100% |
11888
2.22 KIPS |
|
|
Image Classification (I8)
|
100% |
9816
1.84 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17133
286.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
17334
289.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
15882
265.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
175190
212.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
176274
213.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
158028
191.4 IPS |
|
|
Object Detection (F32)
|
100% |
8380
625.6 IPS |
|
|
Object Detection (F16)
|
100% |
8287
618.6 IPS |
|
|
Object Detection (I8)
|
56% |
7641
570.4 IPS |
|
|
Face Detection (F32)
|
100% |
36667
436.0 IPS |
|
|
Face Detection (F16)
|
100% |
37920
450.9 IPS |
|
|
Face Detection (I8)
|
89% |
31612
375.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
71161
551.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
67247
521.5 IPS |
|
|
Depth Estimation (I8)
|
94% |
54143
419.9 IPS |
|
|
Style Transfer (F32)
|
100% |
312106
410.5 IPS |
|
|
Style Transfer (F16)
|
100% |
312821
411.5 IPS |
|
|
Style Transfer (I8)
|
98% |
270578
355.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
43884
1.57 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
41035
1.47 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
32833
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
3014
4.33 KIPS |
|
|
Text Classification (F16)
|
100% |
3015
4.33 KIPS |
|
|
Text Classification (I8)
|
98% |
1839
2.64 KIPS |
|
|
Machine Translation (F32)
|
100% |
4964
91.3 IPS |
|
|
Machine Translation (F16)
|
100% |
4976
91.6 IPS |
|
|
Machine Translation (I8)
|
70% |
2816
51.8 IPS |
