Xiaomi Redmi Note 7
Geekbench AI Score
14
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 07:36 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
1.54 KIPS |
|
|
Image Classification (HP)
|
0% |
0
1.49 KIPS |
|
|
Image Classification (Q)
|
0% |
0
2.13 KIPS |
|
|
Image Segmentation (SP)
|
73% |
9338
161.4 IPS |
|
|
Image Segmentation (HP)
|
73% |
9173
158.5 IPS |
|
|
Image Segmentation (Q)
|
73% |
22221
384.0 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
499.9 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
503.3 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
1.16 KIPS |
|
|
Object Detection (SP)
|
0% |
0
690.3 IPS |
|
|
Object Detection (HP)
|
0% |
0
687.1 IPS |
|
|
Object Detection (Q)
|
0% |
0
530.4 IPS |
|
|
Face Detection (SP)
|
0% |
0
232.2 IPS |
|
|
Face Detection (HP)
|
0% |
0
232.0 IPS |
|
|
Face Detection (Q)
|
0% |
0
359.4 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
504.8 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
492.6 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
442.0 IPS |
|
|
Style Transfer (SP)
|
32% |
78197
980.8 IPS |
|
|
Style Transfer (HP)
|
32% |
76030
953.6 IPS |
|
|
Style Transfer (Q)
|
0% |
0
2.69 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
1.09 KIPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
2% |
173
2.04 KIPS |
|
|
Text Classification (SP)
|
29% |
404
6.98 KIPS |
|
|
Text Classification (HP)
|
29% |
400
6.91 KIPS |
|
|
Text Classification (Q)
|
29% |
274
4.73 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
4.68 IPS |
|
|
Machine Translation (HP)
|
0% |
0
4.66 IPS |
|
|
Machine Translation (Q)
|
0% |
0
3.77 IPS |
