FPT Elead F22FAH Generic
Geekbench AI Score
3426
Single Precision Score
3436
Half Precision Score
5140
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | rennsport |
| Upload Date | April 18 2025 03:53 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-10400 CPU @ 2.90GHz |
| 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 | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2135
397.1 IPS |
|
|
Image Classification (HP)
|
100% |
2172
404.0 IPS |
|
|
Image Classification (Q)
|
100% |
3247
603.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2143
34.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2138
34.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3617
58.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4517
5.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
4523
5.28 IPS |
|
|
Pose Estimation (Q)
|
94% |
8919
10.5 IPS |
|
|
Object Detection (SP)
|
100% |
2098
166.4 IPS |
|
|
Object Detection (HP)
|
100% |
2107
167.1 IPS |
|
|
Object Detection (Q)
|
87% |
3381
271.2 IPS |
|
|
Face Detection (SP)
|
100% |
3731
44.3 IPS |
|
|
Face Detection (HP)
|
100% |
3735
44.4 IPS |
|
|
Face Detection (Q)
|
97% |
8901
106.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5706
44.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
5766
44.4 IPS |
|
|
Depth Estimation (Q)
|
81% |
9369
74.0 IPS |
|
|
Style Transfer (SP)
|
100% |
13083
16.8 IPS |
|
|
Style Transfer (HP)
|
100% |
13088
16.8 IPS |
|
|
Style Transfer (Q)
|
98% |
25217
32.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2665
98.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2660
98.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
5218
193.3 IPS |
|
|
Text Classification (SP)
|
100% |
2262
3.02 KIPS |
|
|
Text Classification (HP)
|
100% |
2243
2.99 KIPS |
|
|
Text Classification (Q)
|
91% |
1078
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
3069
52.9 IPS |
|
|
Machine Translation (HP)
|
100% |
3082
53.1 IPS |
|
|
Machine Translation (Q)
|
100% |
3074
53.0 IPS |
