LENOVO 81WD
Geekbench AI Score
1373
Single Precision Score
717
Half Precision Score
2853
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | OMAlotaibi |
| Upload Date | April 08 2025 04:56 AM |
| Views | 19 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-1035G1 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 81WD |
| Motherboard | LENOVO LNVNB161216 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-1035G1 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 126 Stepping 5 |
| Base Frequency | 1.19 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1036
192.6 IPS |
|
|
Image Classification (HP)
|
100% |
295
54.8 IPS |
|
|
Image Classification (Q)
|
99% |
2763
515.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
525
8.51 IPS |
|
|
Image Segmentation (HP)
|
100% |
382
6.20 IPS |
|
|
Image Segmentation (Q)
|
98% |
1763
28.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2407
2.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
1741
2.03 IPS |
|
|
Pose Estimation (Q)
|
94% |
7726
9.06 IPS |
|
|
Object Detection (SP)
|
100% |
951
75.4 IPS |
|
|
Object Detection (HP)
|
100% |
351
27.8 IPS |
|
|
Object Detection (Q)
|
86% |
2610
209.7 IPS |
|
|
Face Detection (SP)
|
100% |
1266
15.0 IPS |
|
|
Face Detection (HP)
|
100% |
623
7.40 IPS |
|
|
Face Detection (Q)
|
97% |
3554
42.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
2766
21.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1081
8.33 IPS |
|
|
Depth Estimation (Q)
|
78% |
6184
49.3 IPS |
|
|
Style Transfer (SP)
|
100% |
5179
6.66 IPS |
|
|
Style Transfer (HP)
|
100% |
4425
5.69 IPS |
|
|
Style Transfer (Q)
|
98% |
5984
7.72 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1017
37.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
765
28.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2069
76.6 IPS |
|
|
Text Classification (SP)
|
100% |
1067
1.42 KIPS |
|
|
Text Classification (HP)
|
100% |
591
789.0 IPS |
|
|
Text Classification (Q)
|
97% |
1101
1.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
973
16.8 IPS |
|
|
Machine Translation (HP)
|
100% |
389
6.70 IPS |
|
|
Machine Translation (Q)
|
65% |
1217
24.5 IPS |
