LENOVO 90UT001AUS
Geekbench ML Score
12393
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 26 2024 07:31 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | LENOVO 90UT001AUS |
| Motherboard | LENOVO 3769 |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel Core i5-14400F |
| Topology | 1 Processor, 10 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 191 Stepping 2 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 20.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4060 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5156
964.8 IPS |
|
|
Image Classification (F16)
|
100% |
5377
1.01 KIPS |
|
|
Image Classification (I8)
|
100% |
4829
903.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
9274
154.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
8678
144.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
8238
137.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
80099
97.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
79409
96.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
70899
85.9 IPS |
|
|
Object Detection (F32)
|
100% |
4501
336.0 IPS |
|
|
Object Detection (F16)
|
100% |
4579
341.9 IPS |
|
|
Object Detection (I8)
|
61% |
4265
318.4 IPS |
|
|
Face Detection (F32)
|
100% |
14891
177.1 IPS |
|
|
Face Detection (F16)
|
100% |
15725
187.0 IPS |
|
|
Face Detection (I8)
|
89% |
13274
157.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
35049
271.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
33290
258.2 IPS |
|
|
Depth Estimation (I8)
|
94% |
26986
209.3 IPS |
|
|
Style Transfer (F32)
|
100% |
117153
154.1 IPS |
|
|
Style Transfer (F16)
|
100% |
121227
159.5 IPS |
|
|
Style Transfer (I8)
|
98% |
107696
141.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
20918
747.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
20717
739.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
13258
473.5 IPS |
|
|
Text Classification (F32)
|
100% |
2789
4.01 KIPS |
|
|
Text Classification (F16)
|
100% |
2791
4.01 KIPS |
|
|
Text Classification (I8)
|
98% |
1587
2.28 KIPS |
|
|
Machine Translation (F32)
|
100% |
3058
56.3 IPS |
|
|
Machine Translation (F16)
|
100% |
3059
56.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1785
32.9 IPS |
