LENOVO 21FA0052US
Geekbench AI Score
20046
Single Precision Score
31994
Half Precision Score
15336
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| Upload Date | August 17 2024 09:20 PM |
| Views | 19 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX 3500 Ada Generation Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 21FA0052US |
| Motherboard | LENOVO 21FA0052US |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-14700HX |
| Topology | 1 Processor, 20 Cores, 28 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7653
1.42 KIPS |
|
|
Image Classification (HP)
|
99% |
12775
2.38 KIPS |
|
|
Image Classification (Q)
|
100% |
6967
1.30 KIPS |
|
|
Image Segmentation (SP)
|
100% |
13148
213.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
17622
285.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
11840
192.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
118451
138.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
335056
391.0 IPS |
|
|
Pose Estimation (Q)
|
97% |
109201
127.9 IPS |
|
|
Object Detection (SP)
|
100% |
9396
745.3 IPS |
|
|
Object Detection (HP)
|
100% |
15269
1.21 KIPS |
|
|
Object Detection (Q)
|
88% |
8251
661.7 IPS |
|
|
Face Detection (SP)
|
100% |
24072
286.0 IPS |
|
|
Face Detection (HP)
|
100% |
32979
391.9 IPS |
|
|
Face Detection (Q)
|
97% |
20658
246.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
44562
343.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
82601
636.4 IPS |
|
|
Depth Estimation (Q)
|
70% |
35304
295.5 IPS |
|
|
Style Transfer (SP)
|
100% |
191121
245.7 IPS |
|
|
Style Transfer (HP)
|
100% |
456623
587.0 IPS |
|
|
Style Transfer (Q)
|
98% |
176028
227.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37300
1.38 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
49050
1.81 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
25170
932.0 IPS |
|
|
Text Classification (SP)
|
100% |
3292
4.39 KIPS |
|
|
Text Classification (HP)
|
99% |
4210
5.62 KIPS |
|
|
Text Classification (Q)
|
97% |
1800
2.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3717
64.0 IPS |
|
|
Machine Translation (HP)
|
100% |
3799
65.4 IPS |
|
|
Machine Translation (Q)
|
60% |
1665
37.1 IPS |
