LENOVO TB350FU
Geekbench ML Score
180
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:06 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | LENOVO TB350FU |
| Model ID | LENOVO TB350FU |
| Motherboard | tulip_row_wifi |
| 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 | 5.69 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
34
6.44 IPS |
|
|
Image Classification (F16)
|
100% |
123
22.9 IPS |
|
|
Image Classification (I8)
|
97% |
249
46.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
260
4.34 IPS |
|
|
Image Segmentation (F16)
|
100% |
253
4.22 IPS |
|
|
Image Segmentation (I8)
|
98% |
385
6.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
258
0.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
338
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1445
1.75 IPS |
|
|
Object Detection (F32)
|
100% |
77
5.78 IPS |
|
|
Object Detection (F16)
|
100% |
74
5.56 IPS |
|
|
Object Detection (I8)
|
61% |
265
19.8 IPS |
|
|
Face Detection (F32)
|
100% |
146
1.74 IPS |
|
|
Face Detection (F16)
|
100% |
264
3.14 IPS |
|
|
Face Detection (I8)
|
86% |
684
8.13 IPS |
|
|
Depth Estimation (F32)
|
100% |
319
2.47 IPS |
|
|
Depth Estimation (F16)
|
100% |
180
1.40 IPS |
|
|
Depth Estimation (I8)
|
95% |
232
1.80 IPS |
|
|
Style Transfer (F32)
|
100% |
323
0.42 IPS |
|
|
Style Transfer (F16)
|
100% |
387
0.51 IPS |
|
|
Style Transfer (I8)
|
98% |
973
1.28 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
69
2.47 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
51
1.84 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
105
3.75 IPS |
|
|
Text Classification (F32)
|
100% |
21
30.1 IPS |
|
|
Text Classification (F16)
|
100% |
14
19.7 IPS |
|
|
Text Classification (I8)
|
92% |
96
137.9 IPS |
|
|
Machine Translation (F32)
|
100% |
298
5.49 IPS |
|
|
Machine Translation (F16)
|
100% |
315
5.80 IPS |
|
|
Machine Translation (I8)
|
64% |
218
4.02 IPS |
