Xiaomi Redmi Note 7
Geekbench AI Score
13
Single Precision Score
13
Half Precision Score
7
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 22 2025 08:00 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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)
|
0% |
0
1.37 KIPS |
|
|
Image Classification (HP)
|
0% |
0
1.41 KIPS |
|
|
Image Classification (Q)
|
0% |
0
1.90 KIPS |
|
|
Image Segmentation (SP)
|
73% |
9015
155.8 IPS |
|
|
Image Segmentation (HP)
|
73% |
9089
157.1 IPS |
|
|
Image Segmentation (Q)
|
73% |
21274
367.6 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
480.1 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
487.8 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
1.05 KIPS |
|
|
Object Detection (SP)
|
0% |
0
673.9 IPS |
|
|
Object Detection (HP)
|
0% |
0
651.5 IPS |
|
|
Object Detection (Q)
|
0% |
0
527.0 IPS |
|
|
Face Detection (SP)
|
0% |
0
228.3 IPS |
|
|
Face Detection (HP)
|
0% |
0
227.7 IPS |
|
|
Face Detection (Q)
|
0% |
0
346.4 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
468.7 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
472.3 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
418.5 IPS |
|
|
Style Transfer (SP)
|
32% |
75556
947.7 IPS |
|
|
Style Transfer (HP)
|
32% |
75270
944.1 IPS |
|
|
Style Transfer (Q)
|
0% |
0
2.64 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
1.07 KIPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
2% |
167
1.97 KIPS |
|
|
Text Classification (SP)
|
29% |
389
6.72 KIPS |
|
|
Text Classification (HP)
|
29% |
381
6.58 KIPS |
|
|
Text Classification (Q)
|
29% |
268
4.63 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
4.57 IPS |
|
|
Machine Translation (HP)
|
0% |
0
4.55 IPS |
|
|
Machine Translation (Q)
|
0% |
0
3.68 IPS |
