LENOVO 83F5
Geekbench AI Score
35318
Single Precision Score
60349
Half Precision Score
27166
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | 1ikhan |
| Upload Date | August 29 2025 12:46 AM |
| Views | 13 |
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% |
14082
2.62 KIPS |
|
|
Image Classification (HP)
|
100% |
21386
3.98 KIPS |
|
|
Image Classification (Q)
|
100% |
12402
2.31 KIPS |
|
|
Image Segmentation (SP)
|
100% |
27118
439.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
38667
626.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
24451
397.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
221805
258.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
665574
776.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
184441
216.0 IPS |
|
|
Object Detection (SP)
|
100% |
18232
1.45 KIPS |
|
|
Object Detection (HP)
|
100% |
27690
2.20 KIPS |
|
|
Object Detection (Q)
|
86% |
15725
1.26 KIPS |
|
|
Face Detection (SP)
|
100% |
51968
617.5 IPS |
|
|
Face Detection (HP)
|
100% |
76757
912.0 IPS |
|
|
Face Detection (Q)
|
97% |
43088
513.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
84470
650.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
172235
1.33 KIPS |
|
|
Depth Estimation (Q)
|
78% |
65571
523.6 IPS |
|
|
Style Transfer (SP)
|
100% |
318199
409.0 IPS |
|
|
Style Transfer (HP)
|
100% |
1028436
1.32 KIPS |
|
|
Style Transfer (Q)
|
98% |
282611
364.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
50384
1.86 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
82801
3.06 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
39362
1.46 KIPS |
|
|
Text Classification (SP)
|
100% |
3899
5.20 KIPS |
|
|
Text Classification (HP)
|
100% |
5198
6.94 KIPS |
|
|
Text Classification (Q)
|
97% |
2515
3.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
7127
122.8 IPS |
|
|
Machine Translation (HP)
|
100% |
7186
123.8 IPS |
|
|
Machine Translation (Q)
|
70% |
3149
59.1 IPS |
