LENOVO INVALID
Geekbench AI Score
679
Single Precision Score
359
Half Precision Score
843
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | October 25 2025 10:37 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-4710HQ |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Home Single Language (64-bit) |
| Model | LENOVO INVALID |
| Motherboard | LENOVO LENOVO IDEAPAD Y40-70 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-4710HQ |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
525
97.6 IPS |
|
|
Image Classification (HP)
|
100% |
160
29.7 IPS |
|
|
Image Classification (Q)
|
96% |
695
129.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
328
5.31 IPS |
|
|
Image Segmentation (HP)
|
100% |
236
3.83 IPS |
|
|
Image Segmentation (Q)
|
97% |
617
10.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
786
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
629
0.73 IPS |
|
|
Pose Estimation (Q)
|
86% |
1251
1.48 IPS |
|
|
Object Detection (SP)
|
100% |
370
29.3 IPS |
|
|
Object Detection (HP)
|
100% |
201
15.9 IPS |
|
|
Object Detection (Q)
|
58% |
473
51.6 IPS |
|
|
Face Detection (SP)
|
100% |
1191
14.1 IPS |
|
|
Face Detection (HP)
|
100% |
438
5.20 IPS |
|
|
Face Detection (Q)
|
96% |
1511
18.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1323
10.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
556
4.28 IPS |
|
|
Depth Estimation (Q)
|
78% |
1655
13.2 IPS |
|
|
Style Transfer (SP)
|
100% |
1992
2.56 IPS |
|
|
Style Transfer (HP)
|
100% |
1492
1.92 IPS |
|
|
Style Transfer (Q)
|
87% |
3284
4.27 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
512
18.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
326
12.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
727
27.0 IPS |
|
|
Text Classification (SP)
|
100% |
476
635.7 IPS |
|
|
Text Classification (HP)
|
100% |
252
335.8 IPS |
|
|
Text Classification (Q)
|
97% |
171
229.1 IPS |
|
|
Machine Translation (SP)
|
100% |
546
9.40 IPS |
|
|
Machine Translation (HP)
|
100% |
254
4.37 IPS |
|
|
Machine Translation (Q)
|
68% |
702
13.6 IPS |
