AZW ME mini
Geekbench AI Score
1195
Single Precision Score
1960
Half Precision Score
2835
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | theofficialgman |
| Upload Date | December 13 2025 05:36 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Ubuntu 25.10 |
| Model | AZW ME mini |
| Motherboard | AZW ME mini |
| CPU Information | |
|---|---|
| Name | Intel(R) N150 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 190 Stepping 0 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 11.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
769
142.9 IPS |
|
|
Image Classification (HP)
|
100% |
1225
227.8 IPS |
|
|
Image Classification (Q)
|
99% |
1736
323.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1011
16.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2115
34.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
2129
34.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2053
2.39 IPS |
|
|
Pose Estimation (HP)
|
99% |
1799
2.10 IPS |
|
|
Pose Estimation (Q)
|
97% |
6118
7.16 IPS |
|
|
Object Detection (SP)
|
100% |
715
56.7 IPS |
|
|
Object Detection (HP)
|
99% |
1221
96.9 IPS |
|
|
Object Detection (Q)
|
90% |
1917
153.3 IPS |
|
|
Face Detection (SP)
|
100% |
1538
18.3 IPS |
|
|
Face Detection (HP)
|
100% |
3297
39.2 IPS |
|
|
Face Detection (Q)
|
100% |
4664
55.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
2336
18.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
4191
32.4 IPS |
|
|
Depth Estimation (Q)
|
89% |
5482
42.6 IPS |
|
|
Style Transfer (SP)
|
100% |
5624
7.23 IPS |
|
|
Style Transfer (HP)
|
100% |
8897
11.4 IPS |
|
|
Style Transfer (Q)
|
98% |
14946
19.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1006
37.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1749
64.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2975
110.2 IPS |
|
|
Text Classification (SP)
|
71% |
579
837.7 IPS |
|
|
Text Classification (HP)
|
71% |
722
1.04 KIPS |
|
|
Text Classification (Q)
|
92% |
719
965.3 IPS |
|
|
Machine Translation (SP)
|
100% |
445
7.67 IPS |
|
|
Machine Translation (HP)
|
98% |
951
16.4 IPS |
|
|
Machine Translation (Q)
|
100% |
947
16.3 IPS |
