Neousys Technology Inc. POC-700 Series
Geekbench AI Score
1722
Single Precision Score
1660
Half Precision Score
3442
Quantized Score
Geekbench AI 1.7.0 for Linux AVX2
Result Information
| User | frankholamresearch |
| Upload Date | April 14 2026 11:33 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i3-N305 |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.5 LTS |
| Model | Neousys Technology Inc. POC-700 Series |
| Motherboard | Neousys Technology Inc. POC-700 |
| CPU Information | |
|---|---|
| Name | Intel Core i3-N305 |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 190 Stepping 0 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1013
188.4 IPS |
|
|
Image Classification (HP)
|
100% |
1025
190.7 IPS |
|
|
Image Classification (Q)
|
100% |
2201
409.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1199
19.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1205
19.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
2341
38.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2024
2.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1434
1.67 IPS |
|
|
Pose Estimation (Q)
|
96% |
4722
5.53 IPS |
|
|
Object Detection (SP)
|
100% |
1049
83.2 IPS |
|
|
Object Detection (HP)
|
100% |
1046
83.0 IPS |
|
|
Object Detection (Q)
|
88% |
2181
174.8 IPS |
|
|
Face Detection (SP)
|
100% |
2526
30.0 IPS |
|
|
Face Detection (HP)
|
100% |
2552
30.3 IPS |
|
|
Face Detection (Q)
|
100% |
5649
67.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2652
20.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2588
19.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
5917
46.0 IPS |
|
|
Style Transfer (SP)
|
100% |
5017
6.45 IPS |
|
|
Style Transfer (HP)
|
100% |
5080
6.53 IPS |
|
|
Style Transfer (Q)
|
98% |
14505
18.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1208
44.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1208
44.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2958
109.5 IPS |
|
|
Text Classification (SP)
|
100% |
1209
1.61 KIPS |
|
|
Text Classification (HP)
|
100% |
1212
1.62 KIPS |
|
|
Text Classification (Q)
|
92% |
1715
2.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
1820
31.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1754
30.2 IPS |
|
|
Machine Translation (Q)
|
100% |
1791
30.9 IPS |
