ASUSTeK Computer Inc. F7E
Geekbench AI Score
57
Single Precision Score
52
Half Precision Score
80
Quantized Score
Geekbench AI 1.3.0 for Windows x86 (64-bit)
Result Information
| User | StingerYar |
| Upload Date | September 20 2025 05:06 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Pentium T2330 |
| System Information | |
|---|---|
| Operating System | Windows 10 Enterprise N LTSC (64-bit) |
| Model | ASUSTeK Computer Inc. F7E |
| Motherboard | ASUSTeK Computer Inc. F7E |
| CPU Information | |
|---|---|
| Name | Intel Pentium T2330 |
| Topology | 1 Processor, 2 Cores |
| Identifier | GenuineIntel Family 6 Model 15 Stepping 13 |
| Base Frequency | 1.60 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
| Type | DDR-2 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
35
6.45 IPS |
|
|
Image Classification (HP)
|
100% |
19
3.52 IPS |
|
|
Image Classification (Q)
|
99% |
33
6.11 IPS |
|
|
Image Segmentation (SP)
|
100% |
23
0.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
25
0.40 IPS |
|
|
Image Segmentation (Q)
|
98% |
41
0.67 IPS |
|
|
Pose Estimation (SP)
|
100% |
62
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
85
0.10 IPS |
|
|
Pose Estimation (Q)
|
94% |
121
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
33
2.63 IPS |
|
|
Object Detection (HP)
|
100% |
30
2.35 IPS |
|
|
Object Detection (Q)
|
86% |
54
4.36 IPS |
|
|
Face Detection (SP)
|
100% |
103
1.22 IPS |
|
|
Face Detection (HP)
|
100% |
70
0.84 IPS |
|
|
Face Detection (Q)
|
97% |
156
1.85 IPS |
|
|
Depth Estimation (SP)
|
100% |
88
0.67 IPS |
|
|
Depth Estimation (HP)
|
99% |
83
0.64 IPS |
|
|
Depth Estimation (Q)
|
78% |
132
1.05 IPS |
|
|
Style Transfer (SP)
|
100% |
172
0.22 IPS |
|
|
Style Transfer (HP)
|
100% |
232
0.30 IPS |
|
|
Style Transfer (Q)
|
98% |
273
0.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37
1.38 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50
1.83 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
67
2.48 IPS |
|
|
Text Classification (SP)
|
100% |
61
81.4 IPS |
|
|
Text Classification (HP)
|
100% |
43
57.4 IPS |
|
|
Text Classification (Q)
|
97% |
48
64.9 IPS |
|
|
Machine Translation (SP)
|
100% |
71
1.22 IPS |
|
|
Machine Translation (HP)
|
100% |
45
0.77 IPS |
|
|
Machine Translation (Q)
|
65% |
71
1.43 IPS |
