FCE Rapide 14 on ESSP_D5 board
Geekbench ML Score
449
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 10 2025 08:21 AM |
| Views | 5 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
213
39.9 IPS |
|
|
Image Classification (F16)
|
100% |
216
40.4 IPS |
|
|
Image Classification (I8)
|
97% |
382
71.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
298
4.97 IPS |
|
|
Image Segmentation (F16)
|
100% |
295
4.93 IPS |
|
|
Image Segmentation (I8)
|
98% |
370
6.18 IPS |
|
|
Pose Estimation (F32)
|
100% |
440
0.53 IPS |
|
|
Pose Estimation (F16)
|
100% |
440
0.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
1840
2.23 IPS |
|
|
Object Detection (F32)
|
100% |
228
17.0 IPS |
|
|
Object Detection (F16)
|
100% |
225
16.8 IPS |
|
|
Object Detection (I8)
|
61% |
415
31.0 IPS |
|
|
Face Detection (F32)
|
100% |
527
6.26 IPS |
|
|
Face Detection (F16)
|
100% |
524
6.23 IPS |
|
|
Face Detection (I8)
|
86% |
903
10.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
488
3.78 IPS |
|
|
Depth Estimation (F16)
|
100% |
489
3.80 IPS |
|
|
Depth Estimation (I8)
|
95% |
919
7.13 IPS |
|
|
Style Transfer (F32)
|
100% |
792
1.04 IPS |
|
|
Style Transfer (F16)
|
100% |
792
1.04 IPS |
|
|
Style Transfer (I8)
|
98% |
2280
3.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
277
9.91 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
277
9.88 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
905
32.3 IPS |
|
|
Text Classification (F32)
|
100% |
287
412.5 IPS |
|
|
Text Classification (F16)
|
100% |
285
410.1 IPS |
|
|
Text Classification (I8)
|
92% |
250
359.5 IPS |
|
|
Machine Translation (F32)
|
100% |
543
9.99 IPS |
|
|
Machine Translation (F16)
|
100% |
547
10.1 IPS |
|
|
Machine Translation (I8)
|
64% |
267
4.91 IPS |
