ITEL itel A667LP vs ITEL itel A667LP
| ITEL itel A667LP | ITEL itel A667LP | Difference | |
|---|---|---|---|
| Single Precision | 255 | 255 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Half Precision | 260 | 260 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Quantized | 468 | 468 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Geekbench AI 1.2.0 | Geekbench AI 1.2.0 | ||
System Information
| ITEL itel A667LP | ITEL itel A667LP | |
|---|---|---|
| AI Framework | TensorFlow Lite | TensorFlow Lite |
| AI Backend | CPU | CPU |
| AI Device | ARM ARMv8 | ARM ARMv8 |
| Operating System | Android 14 | Android 14 |
| Model | ITEL itel A667LP | ITEL itel A667LP |
| Processor |
ARM ARMv8 @ 1.20 GHz
1 Processor, 8 Cores |
ARM ARMv8 @ 1.20 GHz
1 Processor, 8 Cores |
| Processor ID | ARM implementer 65 architecture 8 variant 1 part 3333 revision 0 | ARM implementer 65 architecture 8 variant 1 part 3333 revision 0 |
| Motherboard | itel-A667LP | itel-A667LP |
| Memory | 2.75 GB | 2.75 GB |
AI Performance
| ITEL itel A667LP | ITEL itel A667LP | Difference | |
|---|---|---|---|
| Image Classification (SP) | 121 | 121 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Classification (HP) | 129 | 129 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Classification (Q) | 333 | 333 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Segmentation (SP) | 171 | 171 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Segmentation (HP) | 174 | 174 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Segmentation (Q) | 461 | 461 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Pose Estimation (SP) | 538 | 538 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Pose Estimation (HP) | 577 | 577 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Pose Estimation (Q) | 1037 | 1037 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Object Detection (SP) | 131 | 131 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Object Detection (HP) | 132 | 132 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Object Detection (Q) | 325 | 325 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Face Detection (SP) | 350 | 350 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Face Detection (HP) | 349 | 349 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Face Detection (Q) | 819 | 819 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Depth Estimation (SP) | 445 | 445 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Depth Estimation (HP) | 456 | 456 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Depth Estimation (Q) | 918 | 918 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Style Transfer (SP) | 1263 | 1263 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Style Transfer (HP) | 1267 | 1267 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Style Transfer (Q) | 2446 | 2446 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Super-Resolution (SP) | 189 | 189 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Super-Resolution (HP) | 198 | 198 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Image Super-Resolution (Q) | 556 | 556 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Text Classification (SP) | 117 | 117 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Text Classification (HP) | 115 | 115 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Text Classification (Q) | 126 | 126 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Machine Translation (SP) | 188 | 188 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Machine Translation (HP) | 184 | 184 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
| Machine Translation (Q) | 77 | 77 | 100.0% |
| ITEL itel A667LP | |||
| ITEL itel A667LP | |||
