Xiaomi Redmi Note 8 Pro
Geekbench ML Score
81
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 29 2024 08:50 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi Note 8 Pro |
| Model ID | Xiaomi Redmi Note 8 Pro |
| Motherboard | begonia |
| CPU Information | |
|---|---|
| Name | ARM MT6785V/CC |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.05 GHz |
| Memory Information | |
|---|---|
| Size | 5.51 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
36
6.69 IPS |
|
|
Image Classification (F16)
|
100% |
31
5.73 IPS |
|
|
Image Classification (I8)
|
97% |
30
5.64 IPS |
|
|
Image Segmentation (F32)
|
100% |
54
0.90 IPS |
|
|
Image Segmentation (F16)
|
100% |
47
0.79 IPS |
|
|
Image Segmentation (I8)
|
98% |
47
0.78 IPS |
|
|
Pose Estimation (F32)
|
100% |
31
0.04 IPS |
|
|
Pose Estimation (F16)
|
100% |
38
0.05 IPS |
|
|
Pose Estimation (I8)
|
100% |
39
0.05 IPS |
|
|
Object Detection (F32)
|
100% |
47
3.53 IPS |
|
|
Object Detection (F16)
|
100% |
39
2.90 IPS |
|
|
Object Detection (I8)
|
56% |
38
2.84 IPS |
|
|
Face Detection (F32)
|
100% |
157
1.86 IPS |
|
|
Face Detection (F16)
|
98% |
140
1.67 IPS |
|
|
Face Detection (I8)
|
86% |
135
1.61 IPS |
|
|
Depth Estimation (F32)
|
100% |
111
0.86 IPS |
|
|
Depth Estimation (F16)
|
100% |
86
0.67 IPS |
|
|
Depth Estimation (I8)
|
94% |
85
0.66 IPS |
|
|
Style Transfer (F32)
|
100% |
201
0.26 IPS |
|
|
Style Transfer (F16)
|
100% |
189
0.25 IPS |
|
|
Style Transfer (I8)
|
98% |
189
0.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
63
2.27 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
51
1.82 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
51
1.81 IPS |
|
|
Text Classification (F32)
|
100% |
134
192.5 IPS |
|
|
Text Classification (F16)
|
100% |
134
192.1 IPS |
|
|
Text Classification (I8)
|
92% |
223
321.1 IPS |
|
|
Machine Translation (F32)
|
100% |
251
4.62 IPS |
|
|
Machine Translation (F16)
|
100% |
253
4.65 IPS |
|
|
Machine Translation (I8)
|
64% |
257
4.74 IPS |
