LENOVO 21FV0029US
Geekbench AI Score
2872
Single Precision Score
1127
Half Precision Score
4864
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | Deslok |
| Upload Date | January 19 2025 12:24 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-13700H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 21FV0029US |
| Motherboard | LENOVO 21FV0029US |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13700H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2484
462.0 IPS |
|
|
Image Classification (HP)
|
100% |
450
83.6 IPS |
|
|
Image Classification (Q)
|
99% |
4208
784.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1341
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
710
11.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2486
40.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4498
5.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
3037
3.54 IPS |
|
|
Pose Estimation (Q)
|
94% |
14751
17.3 IPS |
|
|
Object Detection (SP)
|
100% |
2093
166.0 IPS |
|
|
Object Detection (HP)
|
100% |
518
41.1 IPS |
|
|
Object Detection (Q)
|
86% |
4392
352.9 IPS |
|
|
Face Detection (SP)
|
100% |
5273
62.7 IPS |
|
|
Face Detection (HP)
|
100% |
1343
16.0 IPS |
|
|
Face Detection (Q)
|
97% |
6741
80.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5893
45.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1599
12.3 IPS |
|
|
Depth Estimation (Q)
|
78% |
10773
86.0 IPS |
|
|
Style Transfer (SP)
|
100% |
10979
14.1 IPS |
|
|
Style Transfer (HP)
|
100% |
7300
9.38 IPS |
|
|
Style Transfer (Q)
|
98% |
17422
22.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1959
72.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1417
52.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2996
110.9 IPS |
|
|
Text Classification (SP)
|
100% |
1213
1.62 KIPS |
|
|
Text Classification (HP)
|
100% |
544
725.9 IPS |
|
|
Text Classification (Q)
|
97% |
1344
1.80 KIPS |
|
|
Machine Translation (SP)
|
100% |
1502
25.9 IPS |
|
|
Machine Translation (HP)
|
100% |
547
9.42 IPS |
|
|
Machine Translation (Q)
|
65% |
2147
43.1 IPS |
