Xiaomi Redmi Note 5A
Geekbench AI Score
152
Single Precision Score
151
Half Precision Score
157
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 10 2025 05:08 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 435 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Xiaomi Redmi Note 5A |
| Model ID | Xiaomi Redmi Note 5A |
| Motherboard | MSM8937 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 4 Cores @ 1.09 GHz |
| Cluster 2 | 4 Cores @ 1.40 GHz |
| Memory Information | |
|---|---|
| Size | 2.74 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
80
14.9 IPS |
|
|
Image Classification (HP)
|
100% |
79
14.7 IPS |
|
|
Image Classification (Q)
|
100% |
113
21.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
96
1.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
92
1.49 IPS |
|
|
Image Segmentation (Q)
|
98% |
149
2.42 IPS |
|
|
Pose Estimation (SP)
|
100% |
373
0.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
378
0.44 IPS |
|
|
Pose Estimation (Q)
|
84% |
242
0.29 IPS |
|
|
Object Detection (SP)
|
100% |
72
5.74 IPS |
|
|
Object Detection (HP)
|
100% |
74
5.89 IPS |
|
|
Object Detection (Q)
|
83% |
108
8.75 IPS |
|
|
Face Detection (SP)
|
100% |
194
2.31 IPS |
|
|
Face Detection (HP)
|
100% |
192
2.28 IPS |
|
|
Face Detection (Q)
|
95% |
280
3.34 IPS |
|
|
Depth Estimation (SP)
|
100% |
262
2.02 IPS |
|
|
Depth Estimation (HP)
|
99% |
270
2.08 IPS |
|
|
Depth Estimation (Q)
|
64% |
249
2.28 IPS |
|
|
Style Transfer (SP)
|
89% |
616
0.80 IPS |
|
|
Style Transfer (HP)
|
89% |
614
0.80 IPS |
|
|
Style Transfer (Q)
|
98% |
580
0.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
126
4.66 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
122
4.51 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
136
5.04 IPS |
|
|
Text Classification (SP)
|
100% |
76
101.1 IPS |
|
|
Text Classification (HP)
|
100% |
78
103.6 IPS |
|
|
Text Classification (Q)
|
88% |
80
108.2 IPS |
|
|
Machine Translation (SP)
|
100% |
109
1.87 IPS |
|
|
Machine Translation (HP)
|
100% |
105
1.82 IPS |
|
|
Machine Translation (Q)
|
50% |
47
1.65 IPS |
