Xiaomi Redmi Note 5
Geekbench AI Score
56
Single Precision Score
85
Half Precision Score
83
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 02 2025 05:46 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Redmi Note 5 |
| Model ID | Xiaomi Redmi Note 5 |
| Motherboard | sdm660 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 2 |
| Base Frequency | 1.61 GHz |
| Cluster 1 | 4 Cores @ 1.61 GHz |
| Cluster 2 | 4 Cores @ 1.80 GHz |
| Memory Information | |
|---|---|
| Size | 2.67 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
32
5.98 IPS |
|
|
Image Classification (HP)
|
100% |
54
10.1 IPS |
|
|
Image Classification (Q)
|
97% |
55
10.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
58
0.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
73
1.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
72
1.17 IPS |
|
|
Pose Estimation (SP)
|
100% |
45
0.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
91
0.11 IPS |
|
|
Pose Estimation (Q)
|
95% |
91
0.11 IPS |
|
|
Object Detection (SP)
|
100% |
26
2.03 IPS |
|
|
Object Detection (HP)
|
100% |
46
3.68 IPS |
|
|
Object Detection (Q)
|
89% |
47
3.75 IPS |
|
|
Face Detection (SP)
|
100% |
107
1.27 IPS |
|
|
Face Detection (HP)
|
100% |
148
1.76 IPS |
|
|
Face Detection (Q)
|
97% |
149
1.77 IPS |
|
|
Depth Estimation (SP)
|
100% |
70
0.54 IPS |
|
|
Depth Estimation (HP)
|
99% |
122
0.94 IPS |
|
|
Depth Estimation (Q)
|
62% |
99
0.94 IPS |
|
|
Style Transfer (SP)
|
100% |
140
0.18 IPS |
|
|
Style Transfer (HP)
|
100% |
248
0.32 IPS |
|
|
Style Transfer (Q)
|
98% |
246
0.32 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
30
1.11 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
57
2.09 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
56
2.08 IPS |
|
|
Text Classification (SP)
|
100% |
51
68.6 IPS |
|
|
Text Classification (HP)
|
100% |
53
70.2 IPS |
|
|
Text Classification (Q)
|
91% |
68
91.7 IPS |
|
|
Machine Translation (SP)
|
100% |
90
1.55 IPS |
|
|
Machine Translation (HP)
|
100% |
92
1.59 IPS |
|
|
Machine Translation (Q)
|
57% |
70
1.70 IPS |
