LENOVO INVALID
Geekbench ML Score
24144
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:01 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% |
11405
2.13 KIPS |
|
|
Image Classification (F16)
|
100% |
11679
2.19 KIPS |
|
|
Image Classification (I8)
|
100% |
9206
1.72 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17271
288.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
17429
291.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
15810
264.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
175525
212.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
175813
212.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
158055
191.4 IPS |
|
|
Object Detection (F32)
|
100% |
8319
621.0 IPS |
|
|
Object Detection (F16)
|
100% |
8342
622.8 IPS |
|
|
Object Detection (I8)
|
56% |
7661
572.0 IPS |
|
|
Face Detection (F32)
|
100% |
36596
435.1 IPS |
|
|
Face Detection (F16)
|
100% |
36843
438.1 IPS |
|
|
Face Detection (I8)
|
89% |
31778
377.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
67790
525.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
67676
524.8 IPS |
|
|
Depth Estimation (I8)
|
94% |
54575
423.2 IPS |
|
|
Style Transfer (F32)
|
100% |
307726
404.8 IPS |
|
|
Style Transfer (F16)
|
100% |
315713
415.3 IPS |
|
|
Style Transfer (I8)
|
98% |
271028
356.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
43949
1.57 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
42187
1.51 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
32523
1.16 KIPS |
|
|
Text Classification (F32)
|
100% |
2971
4.27 KIPS |
|
|
Text Classification (F16)
|
100% |
3050
4.38 KIPS |
|
|
Text Classification (I8)
|
98% |
1846
2.65 KIPS |
|
|
Machine Translation (F32)
|
100% |
5004
92.1 IPS |
|
|
Machine Translation (F16)
|
100% |
5040
92.8 IPS |
|
|
Machine Translation (I8)
|
70% |
2807
51.7 IPS |
