LENOVO INVALID
Geekbench ML Score
24053
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 07:15 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% |
11779
2.20 KIPS |
|
|
Image Classification (F16)
|
100% |
11709
2.19 KIPS |
|
|
Image Classification (I8)
|
100% |
9937
1.86 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17062
285.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
16743
279.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
15635
261.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
175327
212.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
174778
211.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
156617
189.7 IPS |
|
|
Object Detection (F32)
|
100% |
8398
626.9 IPS |
|
|
Object Detection (F16)
|
100% |
8325
621.5 IPS |
|
|
Object Detection (I8)
|
56% |
7548
563.5 IPS |
|
|
Face Detection (F32)
|
100% |
35952
427.5 IPS |
|
|
Face Detection (F16)
|
100% |
37154
441.8 IPS |
|
|
Face Detection (I8)
|
89% |
30887
367.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
71513
554.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
67513
523.6 IPS |
|
|
Depth Estimation (I8)
|
94% |
54593
423.4 IPS |
|
|
Style Transfer (F32)
|
100% |
309509
407.1 IPS |
|
|
Style Transfer (F16)
|
100% |
307469
404.4 IPS |
|
|
Style Transfer (I8)
|
98% |
273151
359.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
43062
1.54 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
44435
1.59 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
32860
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
2980
4.28 KIPS |
|
|
Text Classification (F16)
|
100% |
2840
4.08 KIPS |
|
|
Text Classification (I8)
|
98% |
1825
2.62 KIPS |
|
|
Machine Translation (F32)
|
100% |
4815
88.6 IPS |
|
|
Machine Translation (F16)
|
100% |
4850
89.3 IPS |
|
|
Machine Translation (I8)
|
70% |
2742
50.5 IPS |
