LENOVO 83F5
Geekbench AI Score
34100
Single Precision Score
58210
Half Precision Score
26339
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | 1ikhan |
| Upload Date | August 27 2025 01:06 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (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% |
13517
2.51 KIPS |
|
|
Image Classification (HP)
|
100% |
20913
3.89 KIPS |
|
|
Image Classification (Q)
|
100% |
12003
2.23 KIPS |
|
|
Image Segmentation (SP)
|
100% |
26433
428.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
37168
602.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
23587
383.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
211955
247.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
652168
761.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
180306
211.2 IPS |
|
|
Object Detection (SP)
|
100% |
17602
1.40 KIPS |
|
|
Object Detection (HP)
|
100% |
27244
2.16 KIPS |
|
|
Object Detection (Q)
|
86% |
15073
1.21 KIPS |
|
|
Face Detection (SP)
|
100% |
50523
600.3 IPS |
|
|
Face Detection (HP)
|
100% |
74826
889.1 IPS |
|
|
Face Detection (Q)
|
97% |
42324
504.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
82729
637.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
162191
1.25 KIPS |
|
|
Depth Estimation (Q)
|
78% |
64083
511.7 IPS |
|
|
Style Transfer (SP)
|
100% |
303200
389.8 IPS |
|
|
Style Transfer (HP)
|
100% |
1002486
1.29 KIPS |
|
|
Style Transfer (Q)
|
98% |
268958
346.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
48133
1.78 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
78302
2.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38342
1.42 KIPS |
|
|
Text Classification (SP)
|
100% |
3836
5.12 KIPS |
|
|
Text Classification (HP)
|
100% |
4949
6.61 KIPS |
|
|
Text Classification (Q)
|
97% |
2434
3.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
6816
117.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6860
118.2 IPS |
|
|
Machine Translation (Q)
|
70% |
3068
57.5 IPS |
