LENOVO 90Y80000US
Geekbench AI Score
43455
Single Precision Score
64131
Half Precision Score
32048
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | rjoanglin |
| Upload Date | December 05 2025 03:24 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 90Y80000US |
| Motherboard | LENOVO 3784 |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15486
2.88 KIPS |
|
|
Image Classification (HP)
|
100% |
20436
3.80 KIPS |
|
|
Image Classification (Q)
|
100% |
13335
2.48 KIPS |
|
|
Image Segmentation (SP)
|
100% |
31830
516.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
39186
635.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
29132
473.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
381152
444.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
938131
1.09 KIPS |
|
|
Pose Estimation (Q)
|
96% |
310698
363.9 IPS |
|
|
Object Detection (SP)
|
100% |
21177
1.68 KIPS |
|
|
Object Detection (HP)
|
100% |
26486
2.10 KIPS |
|
|
Object Detection (Q)
|
85% |
17326
1.40 KIPS |
|
|
Face Detection (SP)
|
100% |
64172
762.5 IPS |
|
|
Face Detection (HP)
|
100% |
82865
984.6 IPS |
|
|
Face Detection (Q)
|
97% |
51379
612.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
98622
759.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
177166
1.36 KIPS |
|
|
Depth Estimation (Q)
|
77% |
72956
584.3 IPS |
|
|
Style Transfer (SP)
|
100% |
564587
725.8 IPS |
|
|
Style Transfer (HP)
|
100% |
1534196
1.97 KIPS |
|
|
Style Transfer (Q)
|
98% |
468621
604.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
65404
2.42 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
85056
3.14 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
48232
1.79 KIPS |
|
|
Text Classification (SP)
|
100% |
4105
5.48 KIPS |
|
|
Text Classification (HP)
|
100% |
4851
6.48 KIPS |
|
|
Text Classification (Q)
|
97% |
2243
3.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
6292
108.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6364
109.6 IPS |
|
|
Machine Translation (Q)
|
70% |
2876
54.0 IPS |
