MINIX NEO Z150-0dB
Geekbench AI Score
839
Single Precision Score
442
Half Precision Score
1499
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | December 14 2025 10:20 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) N150 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | MINIX NEO Z150-0dB |
| Motherboard | MINIX NEO Z150-0dB |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel(R) N150 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 190 Stepping 0 |
| Base Frequency | 800 MHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
610
113.5 IPS |
|
|
Image Classification (HP)
|
100% |
213
39.6 IPS |
|
|
Image Classification (Q)
|
99% |
1061
197.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
421
6.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
303
4.91 IPS |
|
|
Image Segmentation (Q)
|
98% |
1316
21.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1039
1.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
713
0.83 IPS |
|
|
Pose Estimation (Q)
|
94% |
2188
2.57 IPS |
|
|
Object Detection (SP)
|
100% |
579
45.9 IPS |
|
|
Object Detection (HP)
|
100% |
221
17.6 IPS |
|
|
Object Detection (Q)
|
86% |
1058
85.0 IPS |
|
|
Face Detection (SP)
|
100% |
1395
16.6 IPS |
|
|
Face Detection (HP)
|
100% |
546
6.49 IPS |
|
|
Face Detection (Q)
|
97% |
2264
27.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1468
11.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
612
4.71 IPS |
|
|
Depth Estimation (Q)
|
78% |
2405
19.2 IPS |
|
|
Style Transfer (SP)
|
100% |
2483
3.19 IPS |
|
|
Style Transfer (HP)
|
100% |
1835
2.36 IPS |
|
|
Style Transfer (Q)
|
98% |
4146
5.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
503
18.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
429
15.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1083
40.1 IPS |
|
|
Text Classification (SP)
|
100% |
526
702.7 IPS |
|
|
Text Classification (HP)
|
100% |
324
432.9 IPS |
|
|
Text Classification (Q)
|
97% |
662
887.0 IPS |
|
|
Machine Translation (SP)
|
100% |
838
14.4 IPS |
|
|
Machine Translation (HP)
|
100% |
331
5.71 IPS |
|
|
Machine Translation (Q)
|
65% |
1096
22.0 IPS |
