FCE Regio2 board
Geekbench ML Score
179
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 09 2025 08:10 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | FCE Regio2 board |
| Model ID | FCE Regio2 board |
| Motherboard | tcc805x_android_avn |
| Governor | performance |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3336 revision 3 |
| Base Frequency | 1.30 GHz |
| Cluster 1 | 4 Cores @ 1.30 GHz |
| Memory Information | |
|---|---|
| Size | 3.08 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
102
19.1 IPS |
|
|
Image Classification (F16)
|
100% |
102
19.2 IPS |
|
|
Image Classification (I8)
|
97% |
128
23.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
130
2.18 IPS |
|
|
Image Segmentation (F16)
|
100% |
132
2.20 IPS |
|
|
Image Segmentation (I8)
|
98% |
133
2.22 IPS |
|
|
Pose Estimation (F32)
|
100% |
163
0.20 IPS |
|
|
Pose Estimation (F16)
|
100% |
163
0.20 IPS |
|
|
Pose Estimation (I8)
|
100% |
351
0.42 IPS |
|
|
Object Detection (F32)
|
100% |
104
7.76 IPS |
|
|
Object Detection (F16)
|
100% |
104
7.76 IPS |
|
|
Object Detection (I8)
|
61% |
144
10.7 IPS |
|
|
Face Detection (F32)
|
100% |
252
3.00 IPS |
|
|
Face Detection (F16)
|
100% |
251
2.98 IPS |
|
|
Face Detection (I8)
|
86% |
342
4.06 IPS |
|
|
Depth Estimation (F32)
|
100% |
193
1.50 IPS |
|
|
Depth Estimation (F16)
|
100% |
193
1.50 IPS |
|
|
Depth Estimation (I8)
|
95% |
336
2.60 IPS |
|
|
Style Transfer (F32)
|
100% |
351
0.46 IPS |
|
|
Style Transfer (F16)
|
100% |
351
0.46 IPS |
|
|
Style Transfer (I8)
|
98% |
761
1.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
115
4.12 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
116
4.13 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
214
7.63 IPS |
|
|
Text Classification (F32)
|
100% |
126
180.8 IPS |
|
|
Text Classification (F16)
|
100% |
127
182.9 IPS |
|
|
Text Classification (I8)
|
92% |
102
146.3 IPS |
|
|
Machine Translation (F32)
|
100% |
247
4.55 IPS |
|
|
Machine Translation (F16)
|
100% |
252
4.63 IPS |
|
|
Machine Translation (I8)
|
64% |
123
2.26 IPS |
