MKS Neo's Protege 21126+F System manufacturer System Product Name
Geekbench AI Score
66
Single Precision Score
62
Half Precision Score
98
Quantized Score
Geekbench AI 1.3.0 for Windows x86 (64-bit)
Result Information
| User | Yegor99 |
| Upload Date | September 14 2025 05:16 PM |
| Views | 10 |
| Notes | Original 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 | 1.00 GB |
| Type | DDR-2 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
37
6.93 IPS |
|
|
Image Classification (HP)
|
100% |
29
5.41 IPS |
|
|
Image Classification (Q)
|
99% |
63
11.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
38
0.61 IPS |
|
|
Image Segmentation (HP)
|
100% |
39
0.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
65
1.06 IPS |
|
|
Pose Estimation (SP)
|
100% |
71
0.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
96
0.11 IPS |
|
|
Pose Estimation (Q)
|
94% |
135
0.16 IPS |
|
|
Object Detection (SP)
|
100% |
37
2.95 IPS |
|
|
Object Detection (HP)
|
100% |
33
2.60 IPS |
|
|
Object Detection (Q)
|
86% |
62
4.97 IPS |
|
|
Face Detection (SP)
|
100% |
113
1.34 IPS |
|
|
Face Detection (HP)
|
100% |
77
0.92 IPS |
|
|
Face Detection (Q)
|
97% |
169
2.01 IPS |
|
|
Depth Estimation (SP)
|
100% |
100
0.77 IPS |
|
|
Depth Estimation (HP)
|
99% |
94
0.72 IPS |
|
|
Depth Estimation (Q)
|
78% |
145
1.16 IPS |
|
|
Style Transfer (SP)
|
100% |
193
0.25 IPS |
|
|
Style Transfer (HP)
|
100% |
263
0.34 IPS |
|
|
Style Transfer (Q)
|
98% |
294
0.38 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
42
1.55 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
55
2.02 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
75
2.77 IPS |
|
|
Text Classification (SP)
|
100% |
69
91.9 IPS |
|
|
Text Classification (HP)
|
100% |
48
63.6 IPS |
|
|
Text Classification (Q)
|
97% |
56
74.6 IPS |
|
|
Machine Translation (SP)
|
100% |
77
1.32 IPS |
|
|
Machine Translation (HP)
|
100% |
49
0.84 IPS |
|
|
Machine Translation (Q)
|
65% |
80
1.61 IPS |
