LENOVO 83DA
Geekbench AI Score
1776
Single Precision Score
1771
Half Precision Score
1251
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | exalted |
| Upload Date | January 22 2025 04:43 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core Ultra 5 125H |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04.1 LTS |
| Model | LENOVO 83DA |
| 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 | 4.50 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.23 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1153
214.4 IPS |
|
|
Image Classification (HP)
|
100% |
1385
257.6 IPS |
|
|
Image Classification (Q)
|
99% |
903
168.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2022
32.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2013
32.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
914
14.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2170
2.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
2201
2.57 IPS |
|
|
Pose Estimation (Q)
|
96% |
2504
2.93 IPS |
|
|
Object Detection (SP)
|
100% |
1432
113.6 IPS |
|
|
Object Detection (HP)
|
100% |
1445
114.6 IPS |
|
|
Object Detection (Q)
|
85% |
936
75.3 IPS |
|
|
Face Detection (SP)
|
100% |
2627
31.2 IPS |
|
|
Face Detection (HP)
|
100% |
2642
31.4 IPS |
|
|
Face Detection (Q)
|
97% |
2079
24.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2254
17.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2160
16.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
1699
15.9 IPS |
|
|
Style Transfer (SP)
|
100% |
3147
4.05 IPS |
|
|
Style Transfer (HP)
|
100% |
3147
4.04 IPS |
|
|
Style Transfer (Q)
|
98% |
4781
6.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1630
60.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1624
60.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1250
46.3 IPS |
|
|
Text Classification (SP)
|
100% |
756
1.01 KIPS |
|
|
Text Classification (HP)
|
100% |
763
1.02 KIPS |
|
|
Text Classification (Q)
|
92% |
478
642.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1879
32.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1540
26.5 IPS |
|
|
Machine Translation (Q)
|
58% |
482
11.3 IPS |
