Lenovo P14s G5 (2024) LENOVO 21G3S17800
Geekbench AI Score
11471
Single Precision Score
21002
Half Precision Score
9059
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | slimg |
| Upload Date | July 03 2025 08:34 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX 500 Ada Generation Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | LENOVO 21G3S17800 |
| Motherboard | LENOVO 21G3S17800 |
| Power Plan | Corporate Power Scheme (Balanced) |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 165H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4666
867.7 IPS |
|
|
Image Classification (HP)
|
99% |
9576
1.79 KIPS |
|
|
Image Classification (Q)
|
99% |
4322
806.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
8589
139.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
13488
218.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
7580
123.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
40975
47.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
127954
149.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
35474
41.6 IPS |
|
|
Object Detection (SP)
|
100% |
5862
464.9 IPS |
|
|
Object Detection (HP)
|
100% |
10752
852.9 IPS |
|
|
Object Detection (Q)
|
84% |
5306
427.9 IPS |
|
|
Face Detection (SP)
|
100% |
11671
138.7 IPS |
|
|
Face Detection (HP)
|
100% |
21891
260.1 IPS |
|
|
Face Detection (Q)
|
97% |
10197
121.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
26593
204.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
53846
414.9 IPS |
|
|
Depth Estimation (Q)
|
77% |
21389
171.4 IPS |
|
|
Style Transfer (SP)
|
100% |
77533
99.7 IPS |
|
|
Style Transfer (HP)
|
100% |
233047
299.6 IPS |
|
|
Style Transfer (Q)
|
98% |
70467
90.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
17382
641.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29941
1.11 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
13278
491.7 IPS |
|
|
Text Classification (SP)
|
100% |
2912
3.89 KIPS |
|
|
Text Classification (HP)
|
99% |
3325
4.44 KIPS |
|
|
Text Classification (Q)
|
97% |
1701
2.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
3365
58.0 IPS |
|
|
Machine Translation (HP)
|
100% |
3436
59.2 IPS |
|
|
Machine Translation (Q)
|
70% |
1740
32.6 IPS |
