FCE Rapide 14 on ESSP_D5 board
Geekbench ML Score
371
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 10 2025 08:27 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | FCE Rapide 14 on ESSP_D5 board |
| Model ID | FCE Rapide 14 on ESSP_D5 board |
| Motherboard | tcc807x_android_avn |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 6.25 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
272
50.9 IPS |
|
|
Image Classification (F16)
|
100% |
498
93.2 IPS |
|
|
Image Classification (I8)
|
97% |
479
89.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
402
6.72 IPS |
|
|
Image Segmentation (F16)
|
100% |
651
10.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
630
10.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
202
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
243
0.29 IPS |
|
|
Pose Estimation (I8)
|
100% |
243
0.29 IPS |
|
|
Object Detection (F32)
|
100% |
206
15.4 IPS |
|
|
Object Detection (F16)
|
100% |
355
26.5 IPS |
|
|
Object Detection (I8)
|
62% |
358
26.7 IPS |
|
|
Face Detection (F32)
|
100% |
910
10.8 IPS |
|
|
Face Detection (F16)
|
98% |
1392
16.6 IPS |
|
|
Face Detection (I8)
|
86% |
1314
15.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
411
3.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
549
4.26 IPS |
|
|
Depth Estimation (I8)
|
95% |
544
4.22 IPS |
|
|
Style Transfer (F32)
|
100% |
833
1.10 IPS |
|
|
Style Transfer (F16)
|
100% |
1222
1.61 IPS |
|
|
Style Transfer (I8)
|
98% |
1222
1.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
260
9.29 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
404
14.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
401
14.3 IPS |
|
|
Text Classification (F32)
|
100% |
73
104.7 IPS |
|
|
Text Classification (F16)
|
100% |
74
106.3 IPS |
|
|
Text Classification (I8)
|
92% |
161
231.6 IPS |
|
|
Machine Translation (F32)
|
100% |
144
2.65 IPS |
|
|
Machine Translation (F16)
|
100% |
146
2.68 IPS |
|
|
Machine Translation (I8)
|
64% |
192
3.54 IPS |
