| Upload Date | October 30 2025 02:06 AM | 
| Views | 1 | 
| AI Information | |
|---|---|
| Framework | TensorFlow Lite | 
| Backend | GPU | 
| Device | ARM ARMv8 | 
| System Information | |
|---|---|
| Operating System | Android 15 | 
| Model | Freeski C109 | 
| Model ID | Freeski C109 | 
| Motherboard | exdroid | 
| CPU Information | |
|---|---|
| Name | ARM ARMv8 | 
| Topology | 1 Processor, 8 Cores | 
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3333 revision 0 | 
| Base Frequency | 1.42 GHz | 
| Cluster 1 | 4 Cores @ 1.42 GHz | 
| Cluster 2 | 4 Cores @ 1.80 GHz | 
| Memory Information | |
|---|---|
| Size | 3.64 GB | 
| Workload | Accuracy | Score | |
|---|---|---|---|
| Image Classification (SP) | 100% | 36 6.76 IPS | |
| Image Classification (HP) | 100% | 68 12.6 IPS | |
| Image Classification (Q) | 99% | 66 12.2 IPS | |
| Image Segmentation (SP) | 100% | 51 0.83 IPS | |
| Image Segmentation (HP) | 100% | 85 1.38 IPS | |
| Image Segmentation (Q) | 98% | 83 1.35 IPS | |
| Pose Estimation (SP) | 100% | 33 0.04 IPS | |
| Pose Estimation (HP) | 100% | 39 0.05 IPS | |
| Pose Estimation (Q) | 96% | 39 0.05 IPS | |
| Object Detection (SP) | 100% | 30 2.38 IPS | |
| Object Detection (HP) | 100% | 51 4.01 IPS | |
| Object Detection (Q) | 83% | 50 4.03 IPS | |
| Face Detection (SP) | 100% | 115 1.37 IPS | |
| Face Detection (HP) | 100% | 177 2.10 IPS | |
| Face Detection (Q) | 97% | 168 2.00 IPS | |
| Depth Estimation (SP) | 100% | 63 0.48 IPS | |
| Depth Estimation (HP) | 99% | 83 0.64 IPS | |
| Depth Estimation (Q) | 62% | 67 0.64 IPS | |
| Style Transfer (SP) | 100% | 126 0.16 IPS | |
| Style Transfer (HP) | 100% | 174 0.22 IPS | |
| Style Transfer (Q) | 98% | 173 0.22 IPS | |
| Image Super-Resolution (SP) | 100% | 33 1.20 IPS | |
| Image Super-Resolution (HP) | 100% | 50 1.84 IPS | |
| Image Super-Resolution (Q) | 97% | 49 1.83 IPS | |
| Text Classification (SP) | 100% | 49 64.9 IPS | |
| Text Classification (HP) | 100% | 49 65.4 IPS | |
| Text Classification (Q) | 91% | 93 124.9 IPS | |
| Machine Translation (SP) | 100% | 82 1.41 IPS | |
| Machine Translation (HP) | 100% | 83 1.42 IPS | |
| Machine Translation (Q) | 57% | 73 1.77 IPS |