LENOVO INVALID
Geekbench ML Score
22633
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:53 AM |
| Views | 3 |
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% |
10694
2.00 KIPS |
|
|
Image Classification (F16)
|
100% |
10916
2.04 KIPS |
|
|
Image Classification (I8)
|
100% |
9277
1.74 KIPS |
|
|
Image Segmentation (F32)
|
100% |
16548
276.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
16470
275.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
14564
243.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
172941
209.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
171547
207.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
153619
186.0 IPS |
|
|
Object Detection (F32)
|
100% |
7929
592.0 IPS |
|
|
Object Detection (F16)
|
100% |
7773
580.3 IPS |
|
|
Object Detection (I8)
|
56% |
7158
534.4 IPS |
|
|
Face Detection (F32)
|
100% |
33541
398.8 IPS |
|
|
Face Detection (F16)
|
100% |
33551
398.9 IPS |
|
|
Face Detection (I8)
|
89% |
29438
350.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
66434
515.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
62737
486.5 IPS |
|
|
Depth Estimation (I8)
|
94% |
51729
401.2 IPS |
|
|
Style Transfer (F32)
|
100% |
304664
400.8 IPS |
|
|
Style Transfer (F16)
|
100% |
292819
385.2 IPS |
|
|
Style Transfer (I8)
|
98% |
243085
319.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
37309
1.33 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
38336
1.37 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
30640
1.09 KIPS |
|
|
Text Classification (F32)
|
100% |
2888
4.15 KIPS |
|
|
Text Classification (F16)
|
100% |
2886
4.15 KIPS |
|
|
Text Classification (I8)
|
98% |
1713
2.46 KIPS |
|
|
Machine Translation (F32)
|
100% |
4578
84.3 IPS |
|
|
Machine Translation (F16)
|
100% |
4485
82.5 IPS |
|
|
Machine Translation (I8)
|
70% |
2552
47.0 IPS |
