LENOVO 83D4
Geekbench ML Score
10576
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 25 2024 08:57 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | LENOVO 83D4 |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 185H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4050 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5239
980.4 IPS |
|
|
Image Classification (F16)
|
100% |
5197
972.5 IPS |
|
|
Image Classification (I8)
|
100% |
4522
846.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
7978
133.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
8073
134.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
7307
122.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
55129
66.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
56469
68.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
48500
58.7 IPS |
|
|
Object Detection (F32)
|
100% |
4325
322.9 IPS |
|
|
Object Detection (F16)
|
100% |
4264
318.3 IPS |
|
|
Object Detection (I8)
|
61% |
2645
197.4 IPS |
|
|
Face Detection (F32)
|
100% |
13837
164.5 IPS |
|
|
Face Detection (F16)
|
100% |
13985
166.3 IPS |
|
|
Face Detection (I8)
|
89% |
11358
135.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
28474
220.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
28168
218.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
24522
190.2 IPS |
|
|
Style Transfer (F32)
|
100% |
95753
126.0 IPS |
|
|
Style Transfer (F16)
|
100% |
90409
118.9 IPS |
|
|
Style Transfer (I8)
|
98% |
84527
111.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
18867
673.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17753
634.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
13941
497.9 IPS |
|
|
Text Classification (F32)
|
100% |
2027
2.91 KIPS |
|
|
Text Classification (F16)
|
100% |
2047
2.94 KIPS |
|
|
Text Classification (I8)
|
98% |
1251
1.80 KIPS |
|
|
Machine Translation (F32)
|
100% |
3014
55.5 IPS |
|
|
Machine Translation (F16)
|
100% |
3038
55.9 IPS |
|
|
Machine Translation (I8)
|
70% |
1794
33.0 IPS |
