FPT Elead F22FAH vs FPT Elead F22FAH
| FPT Elead F22FAH | FPT Elead F22FAH | Difference | |
|---|---|---|---|
| Single Precision | 1304 | 1304 | 100.0% |
| FPT Elead F22FAH | |||
| FPT Elead F22FAH | |||
| Half Precision | 2002 | 2002 | 100.0% |
| FPT Elead F22FAH | |||
| FPT Elead F22FAH | |||
| Quantized | 1898 | 1898 | 100.0% |
| FPT Elead F22FAH | |||
| FPT Elead F22FAH | |||
| Geekbench AI 1.7.0 | Geekbench AI 1.7.0 | ||
System Information
| Generic | Generic | |
|---|---|---|
| AI Framework | OpenVINO | OpenVINO |
| AI Backend | GPU | GPU |
| AI Device | Intel(R) UHD Graphics 630 (iGPU) | Intel(R) UHD Graphics 630 (iGPU) |
| Operating System | Microsoft Windows 10 Pro (64-bit) | Microsoft Windows 10 Pro (64-bit) |
| Model | Generic | Generic |
| Processor |
Intel Core i5-10400 @ 2.90 GHz
1 Processor, 6 Cores, 12 Threads |
Intel Core i5-10400 @ 2.90 GHz
1 Processor, 6 Cores, 12 Threads |
| Processor ID | GenuineIntel Family 6 Model 165 Stepping 3 | GenuineIntel Family 6 Model 165 Stepping 3 |
| Processor Codename | ||
| Processor Package | ||
| Motherboard | ASRock H470M-HDV/M.2 | ASRock H470M-HDV/M.2 |
| Northbridge | ||
| Southbridge | ||
| BIOS | American Megatrends Inc. P1.40 | American Megatrends Inc. P1.40 |
| Memory | 8.00 GB | 8.00 GB |
AI Performance
| Generic | Generic | Difference | |
|---|---|---|---|
| Image Classification (SP) | 819 | 819 | 100.0% |
| Generic | |||
| Generic | |||
| Image Classification (HP) | 1315 | 1315 | 100.0% |
| Generic | |||
| Generic | |||
| Image Classification (Q) | 1209 | 1209 | 100.0% |
| Generic | |||
| Generic | |||
| Image Segmentation (SP) | 985 | 985 | 100.0% |
| Generic | |||
| Generic | |||
| Image Segmentation (HP) | 1752 | 1752 | 100.0% |
| Generic | |||
| Generic | |||
| Image Segmentation (Q) | 1640 | 1640 | 100.0% |
| Generic | |||
| Generic | |||
| Pose Estimation (SP) | 1921 | 1921 | 100.0% |
| Generic | |||
| Generic | |||
| Pose Estimation (HP) | 2061 | 2061 | 100.0% |
| Generic | |||
| Generic | |||
| Pose Estimation (Q) | 2724 | 2724 | 100.0% |
| Generic | |||
| Generic | |||
| Object Detection (SP) | 790 | 790 | 100.0% |
| Generic | |||
| Generic | |||
| Object Detection (HP) | 1294 | 1294 | 100.0% |
| Generic | |||
| Generic | |||
| Object Detection (Q) | 1213 | 1213 | 100.0% |
| Generic | |||
| Generic | |||
| Face Detection (SP) | 1796 | 1796 | 100.0% |
| Generic | |||
| Generic | |||
| Face Detection (HP) | 3516 | 3516 | 100.0% |
| Generic | |||
| Generic | |||
| Face Detection (Q) | 3225 | 3225 | 100.0% |
| Generic | |||
| Generic | |||
| Depth Estimation (SP) | 2419 | 2419 | 100.0% |
| Generic | |||
| Generic | |||
| Depth Estimation (HP) | 4169 | 4169 | 100.0% |
| Generic | |||
| Generic | |||
| Depth Estimation (Q) | 3790 | 3790 | 100.0% |
| Generic | |||
| Generic | |||
| Style Transfer (SP) | 5393 | 5393 | 100.0% |
| Generic | |||
| Generic | |||
| Style Transfer (HP) | 7301 | 7301 | 100.0% |
| Generic | |||
| Generic | |||
| Style Transfer (Q) | 6663 | 6663 | 100.0% |
| Generic | |||
| Generic | |||
| Image Super-Resolution (SP) | 966 | 966 | 100.0% |
| Generic | |||
| Generic | |||
| Image Super-Resolution (HP) | 1782 | 1782 | 100.0% |
| Generic | |||
| Generic | |||
| Image Super-Resolution (Q) | 1696 | 1696 | 100.0% |
| Generic | |||
| Generic | |||
| Text Classification (SP) | 636 | 636 | 100.0% |
| Generic | |||
| Generic | |||
| Text Classification (HP) | 742 | 742 | 100.0% |
| Generic | |||
| Generic | |||
| Text Classification (Q) | 568 | 568 | 100.0% |
| Generic | |||
| Generic | |||
| Machine Translation (SP) | 811 | 811 | 100.0% |
| Generic | |||
| Generic | |||
| Machine Translation (HP) | 1191 | 1191 | 100.0% |
| Generic | |||
| Generic | |||
| Machine Translation (Q) | 1183 | 1183 | 100.0% |
| Generic | |||
| Generic | |||
