LENOVO 20RH001FGE
Geekbench AI Score
1600
Single Precision Score
2316
Half Precision Score
2218
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | bormolino |
| Upload Date | January 11 2025 07:36 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) UHD Graphics 620 (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | LENOVO 20RH001FGE |
| Motherboard | LENOVO 20RH001FGE |
| Power Plan | Ausbalanciert |
| CPU Information | |
|---|---|
| Name | Intel Core i7-8565U |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 12 |
| Base Frequency | 1.99 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1019
189.4 IPS |
|
|
Image Classification (HP)
|
100% |
1540
286.3 IPS |
|
|
Image Classification (Q)
|
100% |
1428
265.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1270
20.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2122
34.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
1974
32.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2603
3.04 IPS |
|
|
Pose Estimation (HP)
|
99% |
2432
2.85 IPS |
|
|
Pose Estimation (Q)
|
97% |
3639
4.26 IPS |
|
|
Object Detection (SP)
|
100% |
990
78.5 IPS |
|
|
Object Detection (HP)
|
99% |
1592
126.7 IPS |
|
|
Object Detection (Q)
|
88% |
1502
120.4 IPS |
|
|
Face Detection (SP)
|
100% |
2664
31.7 IPS |
|
|
Face Detection (HP)
|
100% |
4530
53.8 IPS |
|
|
Face Detection (Q)
|
97% |
4164
49.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
3066
23.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
5143
39.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
4709
36.6 IPS |
|
|
Style Transfer (SP)
|
100% |
7205
9.26 IPS |
|
|
Style Transfer (HP)
|
100% |
9890
12.7 IPS |
|
|
Style Transfer (Q)
|
98% |
8858
11.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1251
46.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2167
80.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2068
76.6 IPS |
|
|
Text Classification (SP)
|
71% |
632
914.4 IPS |
|
|
Text Classification (HP)
|
71% |
757
1.09 KIPS |
|
|
Text Classification (Q)
|
92% |
560
753.0 IPS |
|
|
Machine Translation (SP)
|
100% |
709
12.2 IPS |
|
|
Machine Translation (HP)
|
97% |
930
16.1 IPS |
|
|
Machine Translation (Q)
|
98% |
932
16.1 IPS |
