Xiaomi Redmi Note 7
Geekbench AI Score
79
Single Precision Score
118
Half Precision Score
115
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 22 2025 08:47 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 660 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Redmi Note 7 |
| Model ID | Xiaomi Redmi Note 7 |
| 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 | 1.84 GHz |
| Cluster 1 | 4 Cores @ 1.84 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 3.58 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
47
8.78 IPS |
|
|
Image Classification (HP)
|
100% |
78
14.6 IPS |
|
|
Image Classification (Q)
|
97% |
79
14.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
88
1.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
111
1.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
110
1.79 IPS |
|
|
Pose Estimation (SP)
|
100% |
65
0.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
127
0.15 IPS |
|
|
Pose Estimation (Q)
|
95% |
127
0.15 IPS |
|
|
Object Detection (SP)
|
100% |
37
2.94 IPS |
|
|
Object Detection (HP)
|
100% |
67
5.30 IPS |
|
|
Object Detection (Q)
|
89% |
67
5.38 IPS |
|
|
Face Detection (SP)
|
100% |
159
1.88 IPS |
|
|
Face Detection (HP)
|
100% |
220
2.62 IPS |
|
|
Face Detection (Q)
|
97% |
221
2.63 IPS |
|
|
Depth Estimation (SP)
|
100% |
104
0.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
171
1.32 IPS |
|
|
Depth Estimation (Q)
|
62% |
140
1.33 IPS |
|
|
Style Transfer (SP)
|
100% |
209
0.27 IPS |
|
|
Style Transfer (HP)
|
100% |
346
0.44 IPS |
|
|
Style Transfer (Q)
|
98% |
344
0.44 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
45
1.66 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
81
2.97 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
80
2.96 IPS |
|
|
Text Classification (SP)
|
100% |
62
83.0 IPS |
|
|
Text Classification (HP)
|
100% |
62
83.3 IPS |
|
|
Text Classification (Q)
|
91% |
82
110.7 IPS |
|
|
Machine Translation (SP)
|
100% |
108
1.87 IPS |
|
|
Machine Translation (HP)
|
100% |
110
1.90 IPS |
|
|
Machine Translation (Q)
|
57% |
79
1.92 IPS |
