Xiaomi Redmi Note 7
Geekbench AI Score
13
Single Precision Score
13
Half Precision Score
8
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 21 2025 01:58 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
1.51 KIPS |
|
|
Image Classification (HP)
|
0% |
0
1.56 KIPS |
|
|
Image Classification (Q)
|
0% |
0
2.18 KIPS |
|
|
Image Segmentation (SP)
|
73% |
8755
151.3 IPS |
|
|
Image Segmentation (HP)
|
73% |
8718
150.7 IPS |
|
|
Image Segmentation (Q)
|
73% |
22403
387.2 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
497.6 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
502.4 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
1.15 KIPS |
|
|
Object Detection (SP)
|
0% |
0
686.4 IPS |
|
|
Object Detection (HP)
|
0% |
0
682.2 IPS |
|
|
Object Detection (Q)
|
0% |
0
540.1 IPS |
|
|
Face Detection (SP)
|
0% |
0
230.3 IPS |
|
|
Face Detection (HP)
|
0% |
0
237.2 IPS |
|
|
Face Detection (Q)
|
0% |
0
367.9 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
497.2 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
494.1 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
438.5 IPS |
|
|
Style Transfer (SP)
|
32% |
77200
968.3 IPS |
|
|
Style Transfer (HP)
|
32% |
76750
962.7 IPS |
|
|
Style Transfer (Q)
|
0% |
0
2.63 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
1.13 KIPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
1.11 KIPS |
|
|
Image Super-Resolution (Q)
|
2% |
182
2.15 KIPS |
|
|
Text Classification (SP)
|
29% |
400
6.91 KIPS |
|
|
Text Classification (HP)
|
29% |
390
6.74 KIPS |
|
|
Text Classification (Q)
|
29% |
271
4.67 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
4.75 IPS |
|
|
Machine Translation (HP)
|
0% |
0
4.67 IPS |
|
|
Machine Translation (Q)
|
0% |
0
3.76 IPS |
