TCL T702W
Geekbench ML Score
379
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 25 2024 06:40 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | TCL T702W |
| Model ID | TCL T702W |
| Motherboard | MT6835 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 5.54 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
178
33.4 IPS |
|
|
Image Classification (F16)
|
100% |
180
33.6 IPS |
|
|
Image Classification (I8)
|
97% |
336
62.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
289
4.82 IPS |
|
|
Image Segmentation (F16)
|
100% |
287
4.80 IPS |
|
|
Image Segmentation (I8)
|
98% |
410
6.86 IPS |
|
|
Pose Estimation (F32)
|
100% |
392
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
399
0.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
1750
2.12 IPS |
|
|
Object Detection (F32)
|
100% |
214
16.0 IPS |
|
|
Object Detection (F16)
|
100% |
214
15.9 IPS |
|
|
Object Detection (I8)
|
61% |
426
31.8 IPS |
|
|
Face Detection (F32)
|
100% |
428
5.09 IPS |
|
|
Face Detection (F16)
|
100% |
430
5.11 IPS |
|
|
Face Detection (I8)
|
86% |
882
10.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
423
3.28 IPS |
|
|
Depth Estimation (F16)
|
100% |
421
3.26 IPS |
|
|
Depth Estimation (I8)
|
95% |
839
6.50 IPS |
|
|
Style Transfer (F32)
|
100% |
660
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
661
0.87 IPS |
|
|
Style Transfer (I8)
|
98% |
2005
2.64 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
228
8.15 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
224
7.99 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
238
8.48 IPS |
|
|
Text Classification (F32)
|
100% |
245
352.3 IPS |
|
|
Text Classification (F16)
|
100% |
249
357.6 IPS |
|
|
Text Classification (I8)
|
92% |
194
279.4 IPS |
|
|
Machine Translation (F32)
|
100% |
411
7.57 IPS |
|
|
Machine Translation (F16)
|
100% |
406
7.48 IPS |
|
|
Machine Translation (I8)
|
64% |
232
4.26 IPS |
