Xiaomi Redmi Note 7
Geekbench AI Score
75
Single Precision Score
75
Half Precision Score
113
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 21 2025 05:30 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
42
7.86 IPS |
|
|
Image Classification (HP)
|
100% |
43
7.97 IPS |
|
|
Image Classification (Q)
|
99% |
72
13.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
58
0.95 IPS |
|
|
Image Segmentation (HP)
|
100% |
60
0.97 IPS |
|
|
Image Segmentation (Q)
|
98% |
82
1.34 IPS |
|
|
Pose Estimation (SP)
|
100% |
83
0.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
83
0.10 IPS |
|
|
Pose Estimation (Q)
|
98% |
160
0.19 IPS |
|
|
Object Detection (SP)
|
100% |
44
3.49 IPS |
|
|
Object Detection (HP)
|
100% |
44
3.49 IPS |
|
|
Object Detection (Q)
|
87% |
73
5.88 IPS |
|
|
Face Detection (SP)
|
100% |
112
1.33 IPS |
|
|
Face Detection (HP)
|
100% |
112
1.34 IPS |
|
|
Face Detection (Q)
|
97% |
175
2.08 IPS |
|
|
Depth Estimation (SP)
|
100% |
100
0.77 IPS |
|
|
Depth Estimation (HP)
|
99% |
98
0.76 IPS |
|
|
Depth Estimation (Q)
|
64% |
146
1.32 IPS |
|
|
Style Transfer (SP)
|
100% |
180
0.23 IPS |
|
|
Style Transfer (HP)
|
100% |
174
0.22 IPS |
|
|
Style Transfer (Q)
|
98% |
351
0.45 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
49
1.81 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50
1.84 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
91
3.37 IPS |
|
|
Text Classification (SP)
|
100% |
61
81.6 IPS |
|
|
Text Classification (HP)
|
100% |
61
81.2 IPS |
|
|
Text Classification (Q)
|
91% |
80
107.8 IPS |
|
|
Machine Translation (SP)
|
100% |
107
1.84 IPS |
|
|
Machine Translation (HP)
|
100% |
107
1.83 IPS |
|
|
Machine Translation (Q)
|
57% |
77
1.88 IPS |
