LENOVO 82HS
Geekbench AI Score
682
Single Precision Score
406
Half Precision Score
1685
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | MUNIRA |
| Upload Date | October 19 2025 03:40 PM |
| Views | 24 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-1165G7 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | LENOVO 82HS |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-1165G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 1 |
| Base Frequency | 2.80 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
118
22.0 IPS |
|
|
Image Classification (HP)
|
100% |
63
11.8 IPS |
|
|
Image Classification (Q)
|
99% |
958
178.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
468
7.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
359
5.81 IPS |
|
|
Image Segmentation (Q)
|
98% |
2589
42.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1630
1.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
1002
1.17 IPS |
|
|
Pose Estimation (Q)
|
94% |
2324
2.73 IPS |
|
|
Object Detection (SP)
|
100% |
292
23.2 IPS |
|
|
Object Detection (HP)
|
100% |
108
8.54 IPS |
|
|
Object Detection (Q)
|
86% |
792
63.6 IPS |
|
|
Face Detection (SP)
|
100% |
779
9.26 IPS |
|
|
Face Detection (HP)
|
100% |
248
2.94 IPS |
|
|
Face Detection (Q)
|
97% |
641
7.64 IPS |
|
|
Depth Estimation (SP)
|
100% |
762
5.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
869
6.69 IPS |
|
|
Depth Estimation (Q)
|
78% |
4665
37.2 IPS |
|
|
Style Transfer (SP)
|
100% |
3188
4.10 IPS |
|
|
Style Transfer (HP)
|
100% |
2556
3.29 IPS |
|
|
Style Transfer (Q)
|
98% |
6618
8.53 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
727
26.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
594
21.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1918
71.0 IPS |
|
|
Text Classification (SP)
|
100% |
742
990.3 IPS |
|
|
Text Classification (HP)
|
100% |
445
594.4 IPS |
|
|
Text Classification (Q)
|
97% |
851
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
813
14.0 IPS |
|
|
Machine Translation (HP)
|
100% |
347
5.98 IPS |
|
|
Machine Translation (Q)
|
65% |
1258
25.3 IPS |
