Lenovo-ThinkCentre-M90q-G2-Tiny LENOVO 11MQ002HUS
Geekbench AI Score
2975
Single Precision Score
1324
Half Precision Score
5384
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | aldenyuan |
| Upload Date | March 12 2025 10:45 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-11500 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 11MQ002HUS |
| Motherboard | LENOVO 31A5 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-11500 |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 167 Stepping 1 |
| Base Frequency | 2.71 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2409
448.0 IPS |
|
|
Image Classification (HP)
|
100% |
468
86.9 IPS |
|
|
Image Classification (Q)
|
99% |
5739
1.07 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1224
19.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
710
11.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2478
40.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
5146
6.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
4129
4.82 IPS |
|
|
Pose Estimation (Q)
|
94% |
17018
20.0 IPS |
|
|
Object Detection (SP)
|
100% |
2318
183.9 IPS |
|
|
Object Detection (HP)
|
100% |
596
47.3 IPS |
|
|
Object Detection (Q)
|
86% |
5224
419.8 IPS |
|
|
Face Detection (SP)
|
100% |
4045
48.1 IPS |
|
|
Face Detection (HP)
|
100% |
1295
15.4 IPS |
|
|
Face Detection (Q)
|
97% |
7189
85.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6507
50.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1882
14.5 IPS |
|
|
Depth Estimation (Q)
|
78% |
12347
98.5 IPS |
|
|
Style Transfer (SP)
|
100% |
11715
15.1 IPS |
|
|
Style Transfer (HP)
|
100% |
9190
11.8 IPS |
|
|
Style Transfer (Q)
|
98% |
18364
23.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2179
80.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1846
68.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3140
116.3 IPS |
|
|
Text Classification (SP)
|
100% |
1489
1.99 KIPS |
|
|
Text Classification (HP)
|
100% |
768
1.02 KIPS |
|
|
Text Classification (Q)
|
97% |
1405
1.88 KIPS |
|
|
Machine Translation (SP)
|
100% |
1547
26.6 IPS |
|
|
Machine Translation (HP)
|
100% |
642
11.1 IPS |
|
|
Machine Translation (Q)
|
65% |
2253
45.3 IPS |
