Xiaomi Redmi 9
Geekbench ML Score
121
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | LinFengJun |
| Upload Date | August 18 2024 04:24 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi Redmi 9 |
| Model ID | Xiaomi M2004J19C |
| Motherboard | lancelot |
| CPU Information | |
|---|---|
| Name | ARM MT6769T |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.61 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
70
13.1 IPS |
|
|
Image Classification (F16)
|
100% |
115
21.5 IPS |
|
|
Image Classification (I8)
|
97% |
108
20.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
99
1.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
181
3.02 IPS |
|
|
Image Segmentation (I8)
|
98% |
171
2.86 IPS |
|
|
Pose Estimation (F32)
|
100% |
54
0.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
74
0.09 IPS |
|
|
Pose Estimation (I8)
|
100% |
74
0.09 IPS |
|
|
Object Detection (F32)
|
100% |
54
4.02 IPS |
|
|
Object Detection (F16)
|
100% |
86
6.39 IPS |
|
|
Object Detection (I8)
|
62% |
83
6.20 IPS |
|
|
Face Detection (F32)
|
100% |
222
2.64 IPS |
|
|
Face Detection (F16)
|
98% |
342
4.07 IPS |
|
|
Face Detection (I8)
|
86% |
325
3.86 IPS |
|
|
Depth Estimation (F32)
|
100% |
120
0.93 IPS |
|
|
Depth Estimation (F16)
|
100% |
164
1.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
163
1.27 IPS |
|
|
Style Transfer (F32)
|
100% |
230
0.30 IPS |
|
|
Style Transfer (F16)
|
100% |
348
0.46 IPS |
|
|
Style Transfer (I8)
|
98% |
346
0.46 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
67
2.41 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
102
3.66 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
102
3.63 IPS |
|
|
Text Classification (F32)
|
100% |
63
91.0 IPS |
|
|
Text Classification (F16)
|
100% |
64
91.4 IPS |
|
|
Text Classification (I8)
|
92% |
96
138.0 IPS |
|
|
Machine Translation (F32)
|
100% |
121
2.24 IPS |
|
|
Machine Translation (F16)
|
100% |
121
2.22 IPS |
|
|
Machine Translation (I8)
|
64% |
131
2.41 IPS |
