Tinno Celero3 5G
Geekbench ML Score
278
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 24 2024 11:23 PM |
| Views | 42 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Tinno Celero3 5G |
| Model ID | Tinno Celero3 5G |
| Motherboard | U653DS |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 5.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
157
29.4 IPS |
|
|
Image Classification (F16)
|
100% |
228
42.6 IPS |
|
|
Image Classification (I8)
|
97% |
207
38.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
194
3.23 IPS |
|
|
Image Segmentation (F16)
|
100% |
293
4.89 IPS |
|
|
Image Segmentation (I8)
|
98% |
279
4.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
172
0.21 IPS |
|
|
Pose Estimation (F16)
|
100% |
256
0.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
255
0.31 IPS |
|
|
Object Detection (F32)
|
100% |
127
9.47 IPS |
|
|
Object Detection (F16)
|
100% |
187
14.0 IPS |
|
|
Object Detection (I8)
|
62% |
177
13.3 IPS |
|
|
Face Detection (F32)
|
100% |
351
4.17 IPS |
|
|
Face Detection (F16)
|
98% |
488
5.81 IPS |
|
|
Face Detection (I8)
|
86% |
438
5.21 IPS |
|
|
Depth Estimation (F32)
|
100% |
326
2.53 IPS |
|
|
Depth Estimation (F16)
|
100% |
410
3.18 IPS |
|
|
Depth Estimation (I8)
|
95% |
398
3.09 IPS |
|
|
Style Transfer (F32)
|
100% |
713
0.94 IPS |
|
|
Style Transfer (F16)
|
100% |
998
1.31 IPS |
|
|
Style Transfer (I8)
|
98% |
997
1.31 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
153
5.48 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
214
7.64 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
212
7.56 IPS |
|
|
Text Classification (F32)
|
100% |
161
231.1 IPS |
|
|
Text Classification (F16)
|
100% |
156
223.9 IPS |
|
|
Text Classification (I8)
|
92% |
328
471.4 IPS |
|
|
Machine Translation (F32)
|
100% |
292
5.38 IPS |
|
|
Machine Translation (F16)
|
100% |
293
5.39 IPS |
|
|
Machine Translation (I8)
|
64% |
292
5.38 IPS |
