Xiaomi 21061119BI
Geekbench ML Score
124
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 11:04 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi 21061119BI |
| Model ID | Xiaomi 21061119BI |
| Motherboard | selene |
| CPU Information | |
|---|---|
| Name | ARM MT6769H |
| 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 | 5.58 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
73
13.7 IPS |
|
|
Image Classification (F16)
|
100% |
120
22.5 IPS |
|
|
Image Classification (I8)
|
97% |
115
21.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
107
1.79 IPS |
|
|
Image Segmentation (F16)
|
100% |
183
3.05 IPS |
|
|
Image Segmentation (I8)
|
98% |
173
2.90 IPS |
|
|
Pose Estimation (F32)
|
100% |
57
0.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
79
0.10 IPS |
|
|
Pose Estimation (I8)
|
100% |
79
0.10 IPS |
|
|
Object Detection (F32)
|
100% |
59
4.37 IPS |
|
|
Object Detection (F16)
|
100% |
94
7.01 IPS |
|
|
Object Detection (I8)
|
62% |
87
6.48 IPS |
|
|
Face Detection (F32)
|
100% |
237
2.82 IPS |
|
|
Face Detection (F16)
|
98% |
363
4.32 IPS |
|
|
Face Detection (I8)
|
86% |
340
4.04 IPS |
|
|
Depth Estimation (F32)
|
100% |
126
0.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
175
1.36 IPS |
|
|
Depth Estimation (I8)
|
95% |
174
1.35 IPS |
|
|
Style Transfer (F32)
|
100% |
244
0.32 IPS |
|
|
Style Transfer (F16)
|
100% |
367
0.48 IPS |
|
|
Style Transfer (I8)
|
98% |
366
0.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
71
2.54 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
108
3.87 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
107
3.83 IPS |
|
|
Text Classification (F32)
|
100% |
59
84.9 IPS |
|
|
Text Classification (F16)
|
100% |
59
84.8 IPS |
|
|
Text Classification (I8)
|
92% |
83
119.1 IPS |
|
|
Machine Translation (F32)
|
100% |
113
2.09 IPS |
|
|
Machine Translation (F16)
|
100% |
113
2.09 IPS |
|
|
Machine Translation (I8)
|
64% |
117
2.16 IPS |
