[2015] Mini PC: Giada / Shenzhen Jiehe [F200] To be filled by O.E.M. To be filled by O.E.M.
Geekbench AI Score
90
Single Precision Score
90
Half Precision Score
73
Quantized Score
Geekbench AI 1.2.0 for Windows x86 (64-bit)
Result Information
| User | inc7007 |
| Upload Date | May 07 2025 06:27 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Celeron(R) CPU N2807 @ 1.58GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | To be filled by O.E.M. To be filled by O.E.M. |
| Motherboard | GIADA BayTrail |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Celeron N2807 |
| Topology | 1 Processor, 2 Cores |
| Identifier | GenuineIntel Family 6 Model 55 Stepping 8 |
| Base Frequency | 1.58 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 2.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
60
11.1 IPS |
|
|
Image Classification (HP)
|
100% |
59
10.9 IPS |
|
|
Image Classification (Q)
|
100% |
44
8.17 IPS |
|
|
Image Segmentation (SP)
|
100% |
74
1.19 IPS |
|
|
Image Segmentation (HP)
|
100% |
74
1.20 IPS |
|
|
Image Segmentation (Q)
|
99% |
55
0.90 IPS |
|
|
Pose Estimation (SP)
|
100% |
97
0.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
97
0.11 IPS |
|
|
Pose Estimation (Q)
|
94% |
80
0.09 IPS |
|
|
Object Detection (SP)
|
100% |
55
4.36 IPS |
|
|
Object Detection (HP)
|
100% |
55
4.34 IPS |
|
|
Object Detection (Q)
|
87% |
44
3.50 IPS |
|
|
Face Detection (SP)
|
100% |
187
2.23 IPS |
|
|
Face Detection (HP)
|
100% |
188
2.23 IPS |
|
|
Face Detection (Q)
|
97% |
134
1.60 IPS |
|
|
Depth Estimation (SP)
|
100% |
137
1.06 IPS |
|
|
Depth Estimation (HP)
|
99% |
137
1.06 IPS |
|
|
Depth Estimation (Q)
|
81% |
109
0.86 IPS |
|
|
Style Transfer (SP)
|
100% |
213
0.27 IPS |
|
|
Style Transfer (HP)
|
100% |
210
0.27 IPS |
|
|
Style Transfer (Q)
|
98% |
249
0.32 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
60
2.23 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
60
2.22 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
51
1.87 IPS |
|
|
Text Classification (SP)
|
100% |
54
72.2 IPS |
|
|
Text Classification (HP)
|
100% |
54
72.3 IPS |
|
|
Text Classification (Q)
|
91% |
34
46.1 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (HP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (Q)
|
100% |
86
1.48 IPS |
