TECNO TECNO BF7n
Geekbench ML Score
120
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 12:10 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | TECNO TECNO BF7n |
| Model ID | TECNO TECNO BF7n |
| Motherboard | TECNO-BF7n |
| CPU Information | |
|---|---|
| Name | ARM MT6761V/WBB |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.74 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
59
11.1 IPS |
|
|
Image Classification (F16)
|
100% |
65
12.1 IPS |
|
|
Image Classification (I8)
|
97% |
100
18.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
90
1.51 IPS |
|
|
Image Segmentation (F16)
|
100% |
87
1.46 IPS |
|
|
Image Segmentation (I8)
|
98% |
114
1.90 IPS |
|
|
Pose Estimation (F32)
|
100% |
110
0.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
110
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
239
0.29 IPS |
|
|
Object Detection (F32)
|
100% |
69
5.12 IPS |
|
|
Object Detection (F16)
|
100% |
70
5.23 IPS |
|
|
Object Detection (I8)
|
61% |
110
8.25 IPS |
|
|
Face Detection (F32)
|
100% |
155
1.84 IPS |
|
|
Face Detection (F16)
|
100% |
155
1.84 IPS |
|
|
Face Detection (I8)
|
86% |
273
3.25 IPS |
|
|
Depth Estimation (F32)
|
100% |
139
1.08 IPS |
|
|
Depth Estimation (F16)
|
100% |
131
1.02 IPS |
|
|
Depth Estimation (I8)
|
95% |
254
1.97 IPS |
|
|
Style Transfer (F32)
|
100% |
164
0.22 IPS |
|
|
Style Transfer (F16)
|
100% |
146
0.19 IPS |
|
|
Style Transfer (I8)
|
98% |
413
0.54 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
86
3.09 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
87
3.12 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
175
6.27 IPS |
|
|
Text Classification (F32)
|
100% |
74
107.0 IPS |
|
|
Text Classification (F16)
|
100% |
87
125.0 IPS |
|
|
Text Classification (I8)
|
92% |
92
132.7 IPS |
|
|
Machine Translation (F32)
|
100% |
143
2.63 IPS |
|
|
Machine Translation (F16)
|
100% |
156
2.86 IPS |
|
|
Machine Translation (I8)
|
64% |
100
1.85 IPS |
