LENOVO 83D4
Geekbench AI Score
1265
Single Precision Score
564
Half Precision Score
2117
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | September 21 2025 03:10 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core Ultra 5 125H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | LENOVO 83D4 |
| Motherboard | LENOVO LNVNB161216 |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 5 125H |
| Topology | 1 Processor, 14 Cores, 18 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1354
251.9 IPS |
|
|
Image Classification (HP)
|
100% |
298
55.5 IPS |
|
|
Image Classification (Q)
|
99% |
2930
546.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
815
13.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
401
6.50 IPS |
|
|
Image Segmentation (Q)
|
98% |
1734
28.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2801
3.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
2060
2.40 IPS |
|
|
Pose Estimation (Q)
|
94% |
6095
7.15 IPS |
|
|
Object Detection (SP)
|
100% |
719
57.0 IPS |
|
|
Object Detection (HP)
|
100% |
192
15.3 IPS |
|
|
Object Detection (Q)
|
86% |
1629
131.0 IPS |
|
|
Face Detection (SP)
|
100% |
2377
28.2 IPS |
|
|
Face Detection (HP)
|
100% |
524
6.22 IPS |
|
|
Face Detection (Q)
|
97% |
2662
31.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
2352
18.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
622
4.79 IPS |
|
|
Depth Estimation (Q)
|
78% |
4284
34.2 IPS |
|
|
Style Transfer (SP)
|
100% |
4378
5.63 IPS |
|
|
Style Transfer (HP)
|
100% |
2760
3.55 IPS |
|
|
Style Transfer (Q)
|
98% |
7186
9.27 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
728
26.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
536
19.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1100
40.7 IPS |
|
|
Text Classification (SP)
|
100% |
454
606.6 IPS |
|
|
Text Classification (HP)
|
100% |
216
288.1 IPS |
|
|
Text Classification (Q)
|
97% |
460
616.9 IPS |
|
|
Machine Translation (SP)
|
100% |
586
10.1 IPS |
|
|
Machine Translation (HP)
|
100% |
667
11.5 IPS |
|
|
Machine Translation (Q)
|
65% |
868
17.4 IPS |
