FPT Elead F22FAH Generic
Geekbench AI Score
1304
Single Precision Score
2002
Half Precision Score
1898
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | rennsport |
| Upload Date | March 20 2026 09:22 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) UHD Graphics 630 (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Generic |
| Motherboard | ASRock H470M-HDV/M.2 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10400 |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 3 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
819
152.3 IPS |
|
|
Image Classification (HP)
|
100% |
1315
244.6 IPS |
|
|
Image Classification (Q)
|
100% |
1209
224.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
985
16.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1752
28.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
1640
26.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1921
2.24 IPS |
|
|
Pose Estimation (HP)
|
99% |
2061
2.41 IPS |
|
|
Pose Estimation (Q)
|
97% |
2724
3.19 IPS |
|
|
Object Detection (SP)
|
100% |
790
62.7 IPS |
|
|
Object Detection (HP)
|
99% |
1294
103.0 IPS |
|
|
Object Detection (Q)
|
88% |
1213
97.3 IPS |
|
|
Face Detection (SP)
|
100% |
1796
21.3 IPS |
|
|
Face Detection (HP)
|
100% |
3516
41.8 IPS |
|
|
Face Detection (Q)
|
97% |
3225
38.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
2419
18.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
4169
32.2 IPS |
|
|
Depth Estimation (Q)
|
89% |
3790
29.5 IPS |
|
|
Style Transfer (SP)
|
100% |
5393
6.93 IPS |
|
|
Style Transfer (HP)
|
100% |
7301
9.39 IPS |
|
|
Style Transfer (Q)
|
98% |
6663
8.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
966
35.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1782
65.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1696
62.8 IPS |
|
|
Text Classification (SP)
|
71% |
636
920.3 IPS |
|
|
Text Classification (HP)
|
71% |
742
1.07 KIPS |
|
|
Text Classification (Q)
|
92% |
568
763.2 IPS |
|
|
Machine Translation (SP)
|
100% |
811
14.0 IPS |
|
|
Machine Translation (HP)
|
99% |
1191
20.6 IPS |
|
|
Machine Translation (Q)
|
98% |
1183
20.5 IPS |
