LENOVO INVALID
Geekbench ML Score
22804
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:55 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% |
10531
1.97 KIPS |
|
|
Image Classification (F16)
|
100% |
11004
2.06 KIPS |
|
|
Image Classification (I8)
|
100% |
9278
1.74 KIPS |
|
|
Image Segmentation (F32)
|
100% |
16305
272.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
14642
244.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
15091
252.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
171138
207.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
171697
207.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
154184
186.7 IPS |
|
|
Object Detection (F32)
|
100% |
7959
594.2 IPS |
|
|
Object Detection (F16)
|
100% |
7975
595.4 IPS |
|
|
Object Detection (I8)
|
56% |
7167
535.1 IPS |
|
|
Face Detection (F32)
|
100% |
33828
402.2 IPS |
|
|
Face Detection (F16)
|
100% |
32864
390.8 IPS |
|
|
Face Detection (I8)
|
89% |
27900
331.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
67265
521.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
64717
501.9 IPS |
|
|
Depth Estimation (I8)
|
94% |
51715
401.0 IPS |
|
|
Style Transfer (F32)
|
100% |
289364
380.6 IPS |
|
|
Style Transfer (F16)
|
100% |
300354
395.1 IPS |
|
|
Style Transfer (I8)
|
98% |
269957
355.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
40075
1.43 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
40297
1.44 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
31040
1.11 KIPS |
|
|
Text Classification (F32)
|
100% |
3068
4.41 KIPS |
|
|
Text Classification (F16)
|
100% |
2911
4.18 KIPS |
|
|
Text Classification (I8)
|
98% |
1756
2.52 KIPS |
|
|
Machine Translation (F32)
|
100% |
4565
84.0 IPS |
|
|
Machine Translation (F16)
|
100% |
4516
83.1 IPS |
|
|
Machine Translation (I8)
|
70% |
2597
47.8 IPS |
