LENOVO 83JE
Geekbench ML Score
11112
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | June 29 2025 01:16 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | LENOVO 83JE |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13450HX |
| Topology | 1 Processor, 10 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 191 Stepping 2 |
| Base Frequency | 2.40 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 | 12.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5060 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4504
842.8 IPS |
|
|
Image Classification (F16)
|
100% |
5074
949.5 IPS |
|
|
Image Classification (I8)
|
100% |
4342
812.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
8457
141.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
8628
144.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
7336
122.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
76279
92.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
76946
93.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
71809
87.0 IPS |
|
|
Object Detection (F32)
|
100% |
2715
202.7 IPS |
|
|
Object Detection (F16)
|
100% |
4454
332.5 IPS |
|
|
Object Detection (I8)
|
60% |
3034
226.5 IPS |
|
|
Face Detection (F32)
|
100% |
12544
149.1 IPS |
|
|
Face Detection (F16)
|
100% |
12249
145.6 IPS |
|
|
Face Detection (I8)
|
89% |
13254
157.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
35186
272.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
37037
287.2 IPS |
|
|
Depth Estimation (I8)
|
94% |
30353
235.4 IPS |
|
|
Style Transfer (F32)
|
100% |
122614
161.3 IPS |
|
|
Style Transfer (F16)
|
100% |
120315
158.3 IPS |
|
|
Style Transfer (I8)
|
98% |
106000
139.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
20469
731.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
19213
686.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
17581
627.9 IPS |
|
|
Text Classification (F32)
|
100% |
2580
3.71 KIPS |
|
|
Text Classification (F16)
|
100% |
1900
2.73 KIPS |
|
|
Text Classification (I8)
|
98% |
1214
1.75 KIPS |
|
|
Machine Translation (F32)
|
100% |
2160
39.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2076
38.2 IPS |
|
|
Machine Translation (I8)
|
70% |
1241
22.8 IPS |
