LENOVO 90V6000KUS
Geekbench ML Score
22410
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 26 2024 02:36 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | LENOVO 90V6000KUS |
| Motherboard | LENOVO 376A |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900KF |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 48.0 KB x 16 |
| L2 Cache | 2.00 MB x 4 |
| L3 Cache | 36.0 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% |
11120
2.08 KIPS |
|
|
Image Classification (F16)
|
100% |
11270
2.11 KIPS |
|
|
Image Classification (I8)
|
100% |
9734
1.82 KIPS |
|
|
Image Segmentation (F32)
|
100% |
14808
247.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
14990
250.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
13709
229.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
169780
205.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
169745
205.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
149931
181.6 IPS |
|
|
Object Detection (F32)
|
100% |
7733
577.3 IPS |
|
|
Object Detection (F16)
|
100% |
7739
577.7 IPS |
|
|
Object Detection (I8)
|
56% |
7120
531.5 IPS |
|
|
Face Detection (F32)
|
100% |
32413
385.4 IPS |
|
|
Face Detection (F16)
|
100% |
31194
370.9 IPS |
|
|
Face Detection (I8)
|
89% |
25600
304.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
64165
497.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
61026
473.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
48384
375.2 IPS |
|
|
Style Transfer (F32)
|
100% |
280306
368.7 IPS |
|
|
Style Transfer (F16)
|
100% |
281298
370.0 IPS |
|
|
Style Transfer (I8)
|
98% |
247886
326.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
40570
1.45 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
45076
1.61 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33966
1.21 KIPS |
|
|
Text Classification (F32)
|
100% |
3157
4.54 KIPS |
|
|
Text Classification (F16)
|
100% |
3233
4.65 KIPS |
|
|
Text Classification (I8)
|
98% |
1818
2.61 KIPS |
|
|
Machine Translation (F32)
|
100% |
4283
78.8 IPS |
|
|
Machine Translation (F16)
|
100% |
4285
78.9 IPS |
|
|
Machine Translation (I8)
|
70% |
2353
43.3 IPS |
