LENOVO 82JQ
Geekbench AI Score
1877
Single Precision Score
533
Half Precision Score
2302
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | Petenka315 |
| Upload Date | August 17 2024 02:06 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 5800H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | LENOVO 82JQ |
| Motherboard | LENOVO LNVNB161216 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5800H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1103
205.1 IPS |
|
|
Image Classification (HP)
|
100% |
109
20.3 IPS |
|
|
Image Classification (Q)
|
97% |
2232
416.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1081
17.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
170
2.76 IPS |
|
|
Image Segmentation (Q)
|
97% |
1515
24.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
3268
3.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
2727
3.18 IPS |
|
|
Pose Estimation (Q)
|
87% |
8227
9.72 IPS |
|
|
Object Detection (SP)
|
100% |
1263
100.2 IPS |
|
|
Object Detection (HP)
|
100% |
150
11.9 IPS |
|
|
Object Detection (Q)
|
86% |
1243
99.9 IPS |
|
|
Face Detection (SP)
|
100% |
1818
21.6 IPS |
|
|
Face Detection (HP)
|
100% |
220
2.62 IPS |
|
|
Face Detection (Q)
|
96% |
2948
35.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
3858
29.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
688
5.30 IPS |
|
|
Depth Estimation (Q)
|
76% |
4945
39.8 IPS |
|
|
Style Transfer (SP)
|
100% |
8542
11.0 IPS |
|
|
Style Transfer (HP)
|
100% |
6785
8.72 IPS |
|
|
Style Transfer (Q)
|
87% |
12038
15.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1419
52.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1172
43.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1868
69.2 IPS |
|
|
Text Classification (SP)
|
100% |
1108
1.48 KIPS |
|
|
Text Classification (HP)
|
100% |
456
608.8 IPS |
|
|
Text Classification (Q)
|
97% |
298
398.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1171
20.2 IPS |
|
|
Machine Translation (HP)
|
100% |
447
7.70 IPS |
|
|
Machine Translation (Q)
|
60% |
1241
27.7 IPS |
