LENOVO INVALID
Geekbench ML Score
22511
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 04:45 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% |
10466
1.96 KIPS |
|
|
Image Classification (F16)
|
100% |
10333
1.93 KIPS |
|
|
Image Classification (I8)
|
100% |
8731
1.63 KIPS |
|
|
Image Segmentation (F32)
|
100% |
16904
282.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
16858
281.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
13317
222.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
174417
211.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
170070
205.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
152253
184.4 IPS |
|
|
Object Detection (F32)
|
100% |
7351
548.8 IPS |
|
|
Object Detection (F16)
|
100% |
7860
586.8 IPS |
|
|
Object Detection (I8)
|
56% |
6724
502.0 IPS |
|
|
Face Detection (F32)
|
100% |
34105
405.5 IPS |
|
|
Face Detection (F16)
|
100% |
34293
407.7 IPS |
|
|
Face Detection (I8)
|
89% |
27911
331.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
66789
517.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
63286
490.8 IPS |
|
|
Depth Estimation (I8)
|
94% |
52797
409.4 IPS |
|
|
Style Transfer (F32)
|
100% |
293335
385.9 IPS |
|
|
Style Transfer (F16)
|
100% |
296069
389.5 IPS |
|
|
Style Transfer (I8)
|
98% |
264068
347.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
37994
1.36 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
39657
1.42 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
31001
1.11 KIPS |
|
|
Text Classification (F32)
|
100% |
2832
4.07 KIPS |
|
|
Text Classification (F16)
|
100% |
2999
4.31 KIPS |
|
|
Text Classification (I8)
|
98% |
1762
2.53 KIPS |
|
|
Machine Translation (F32)
|
100% |
4524
83.3 IPS |
|
|
Machine Translation (F16)
|
100% |
4523
83.2 IPS |
|
|
Machine Translation (I8)
|
70% |
2484
45.7 IPS |
