MKS Neo's Protege 21126+F U1 System manufacturer System Product Name
Geekbench AI Score
70
Single Precision Score
67
Half Precision Score
104
Quantized Score
Geekbench AI 1.3.0 for Windows x86 (64-bit)
Result Information
| User | Yegor99 |
| Upload Date | September 14 2025 08:49 PM |
| Views | 12 |
| Notes | Upgrade 1 Windows 10 Pro 22H2 x64 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Pentium E2160 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | System manufacturer System Product Name |
| Motherboard | ASUSTeK Computer INC. P5G-MX |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Pentium E2160 |
| Topology | 1 Processor, 2 Cores |
| Identifier | GenuineIntel Family 6 Model 15 Stepping 13 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
| Type | DDR-2 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
40
7.37 IPS |
|
|
Image Classification (HP)
|
100% |
32
5.93 IPS |
|
|
Image Classification (Q)
|
99% |
65
12.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
41
0.67 IPS |
|
|
Image Segmentation (HP)
|
100% |
43
0.70 IPS |
|
|
Image Segmentation (Q)
|
98% |
71
1.15 IPS |
|
|
Pose Estimation (SP)
|
100% |
72
0.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
99
0.12 IPS |
|
|
Pose Estimation (Q)
|
94% |
141
0.17 IPS |
|
|
Object Detection (SP)
|
100% |
38
3.04 IPS |
|
|
Object Detection (HP)
|
100% |
35
2.78 IPS |
|
|
Object Detection (Q)
|
86% |
63
5.10 IPS |
|
|
Face Detection (SP)
|
100% |
120
1.43 IPS |
|
|
Face Detection (HP)
|
100% |
85
1.00 IPS |
|
|
Face Detection (Q)
|
97% |
185
2.21 IPS |
|
|
Depth Estimation (SP)
|
100% |
102
0.79 IPS |
|
|
Depth Estimation (HP)
|
99% |
99
0.76 IPS |
|
|
Depth Estimation (Q)
|
78% |
155
1.24 IPS |
|
|
Style Transfer (SP)
|
100% |
201
0.26 IPS |
|
|
Style Transfer (HP)
|
100% |
274
0.35 IPS |
|
|
Style Transfer (Q)
|
98% |
325
0.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
44
1.62 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
58
2.16 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
80
2.95 IPS |
|
|
Text Classification (SP)
|
100% |
73
97.1 IPS |
|
|
Text Classification (HP)
|
100% |
52
68.8 IPS |
|
|
Text Classification (Q)
|
97% |
57
76.9 IPS |
|
|
Machine Translation (SP)
|
100% |
88
1.52 IPS |
|
|
Machine Translation (HP)
|
100% |
55
0.95 IPS |
|
|
Machine Translation (Q)
|
65% |
85
1.70 IPS |
