LincPlus LincStation N1
Geekbench AI Score
229
Single Precision Score
218
Half Precision Score
464
Quantized Score
Geekbench AI 1.2.0 for Linux x86 (64-bit)
Result Information
| User | AndyMcSchopf |
| Upload Date | January 07 2025 10:42 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Celeron(R) N5105 @ 2.00GHz |
| System Information | |
|---|---|
| Operating System | Slackware 15.0 x86_64 (post 15.0 -current) |
| Model | LincPlus LincStation N1 |
| Motherboard | Techvision TVI8310X |
| CPU Information | |
|---|---|
| Name | Intel Celeron N5105 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 156 Stepping 0 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.46 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
178
33.1 IPS |
|
|
Image Classification (HP)
|
100% |
178
33.1 IPS |
|
|
Image Classification (Q)
|
100% |
413
76.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
244
3.96 IPS |
|
|
Image Segmentation (HP)
|
100% |
240
3.90 IPS |
|
|
Image Segmentation (Q)
|
99% |
471
7.65 IPS |
|
|
Pose Estimation (SP)
|
100% |
279
0.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
279
0.33 IPS |
|
|
Pose Estimation (Q)
|
94% |
723
0.85 IPS |
|
|
Object Detection (SP)
|
100% |
161
12.7 IPS |
|
|
Object Detection (HP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (Q)
|
87% |
408
32.7 IPS |
|
|
Face Detection (SP)
|
100% |
527
6.26 IPS |
|
|
Face Detection (HP)
|
100% |
526
6.25 IPS |
|
|
Face Detection (Q)
|
97% |
1141
13.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
376
2.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
387
2.98 IPS |
|
|
Depth Estimation (Q)
|
81% |
919
7.26 IPS |
|
|
Style Transfer (SP)
|
100% |
606
0.78 IPS |
|
|
Style Transfer (HP)
|
100% |
606
0.78 IPS |
|
|
Style Transfer (Q)
|
98% |
2482
3.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
183
6.74 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
100
3.68 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
249
9.23 IPS |
|
|
Text Classification (SP)
|
100% |
75
100.8 IPS |
|
|
Text Classification (HP)
|
100% |
75
99.5 IPS |
|
|
Text Classification (Q)
|
91% |
99
132.5 IPS |
|
|
Machine Translation (SP)
|
100% |
124
2.14 IPS |
|
|
Machine Translation (HP)
|
100% |
127
2.19 IPS |
|
|
Machine Translation (Q)
|
100% |
126
2.16 IPS |
