LENOVO 83F5
Geekbench AI Score
30822
Single Precision Score
51632
Half Precision Score
23746
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | September 01 2025 06:04 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | LENOVO 83F5 |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 275HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12102
2.25 KIPS |
|
|
Image Classification (HP)
|
100% |
18588
3.46 KIPS |
|
|
Image Classification (Q)
|
100% |
10495
1.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21903
355.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
30942
501.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
20013
325.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
201537
235.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
594381
693.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
172773
202.4 IPS |
|
|
Object Detection (SP)
|
100% |
16243
1.29 KIPS |
|
|
Object Detection (HP)
|
100% |
24282
1.93 KIPS |
|
|
Object Detection (Q)
|
86% |
14057
1.13 KIPS |
|
|
Face Detection (SP)
|
100% |
46495
552.5 IPS |
|
|
Face Detection (HP)
|
100% |
65172
774.4 IPS |
|
|
Face Detection (Q)
|
97% |
34558
412.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
79957
616.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
158218
1.22 KIPS |
|
|
Depth Estimation (Q)
|
78% |
60920
486.5 IPS |
|
|
Style Transfer (SP)
|
100% |
299947
385.6 IPS |
|
|
Style Transfer (HP)
|
100% |
899555
1.16 KIPS |
|
|
Style Transfer (Q)
|
98% |
267258
344.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
44660
1.65 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
78252
2.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36383
1.35 KIPS |
|
|
Text Classification (SP)
|
100% |
3252
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
3990
5.33 KIPS |
|
|
Text Classification (Q)
|
97% |
2094
2.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
5507
94.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5601
96.5 IPS |
|
|
Machine Translation (Q)
|
70% |
2607
48.9 IPS |
