LENOVO 83DA
Geekbench AI Score
8089
Single Precision Score
12367
Half Precision Score
18277
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | exalted |
| Upload Date | April 10 2025 01:37 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | LENOVO 83DA |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| 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 | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5797
1.08 KIPS |
|
|
Image Classification (HP)
|
100% |
7615
1.42 KIPS |
|
|
Image Classification (Q)
|
100% |
9374
1.74 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4749
77.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
12486
202.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
18438
298.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
21829
25.5 IPS |
|
|
Pose Estimation (HP)
|
99% |
19218
22.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
67005
78.4 IPS |
|
|
Object Detection (SP)
|
100% |
4958
393.3 IPS |
|
|
Object Detection (HP)
|
100% |
7948
630.4 IPS |
|
|
Object Detection (Q)
|
88% |
12150
973.6 IPS |
|
|
Face Detection (SP)
|
100% |
9641
114.6 IPS |
|
|
Face Detection (HP)
|
100% |
18956
225.2 IPS |
|
|
Face Detection (Q)
|
100% |
28092
333.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
19992
154.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
34641
267.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
38380
298.3 IPS |
|
|
Style Transfer (SP)
|
100% |
52871
68.0 IPS |
|
|
Style Transfer (HP)
|
100% |
69812
89.7 IPS |
|
|
Style Transfer (Q)
|
98% |
153754
198.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9219
340.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
15723
580.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
20616
763.5 IPS |
|
|
Text Classification (SP)
|
71% |
1668
2.41 KIPS |
|
|
Text Classification (HP)
|
71% |
2411
3.49 KIPS |
|
|
Text Classification (Q)
|
92% |
2544
3.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
2571
44.3 IPS |
|
|
Machine Translation (HP)
|
96% |
3316
57.3 IPS |
|
|
Machine Translation (Q)
|
100% |
3401
58.6 IPS |
