Xiaomi Redmi Note 8
Geekbench AI Score
311
Single Precision Score
312
Half Precision Score
330
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 22 2025 07:54 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 665 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Redmi Note 8 |
| Model ID | Xiaomi Redmi Note 8 |
| Motherboard | trinket |
| 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 | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 3.56 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
162
30.2 IPS |
|
|
Image Classification (HP)
|
100% |
159
29.6 IPS |
|
|
Image Classification (Q)
|
100% |
216
40.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
180
2.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
212
3.44 IPS |
|
|
Image Segmentation (Q)
|
98% |
301
4.89 IPS |
|
|
Pose Estimation (SP)
|
100% |
713
0.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
699
0.82 IPS |
|
|
Pose Estimation (Q)
|
84% |
522
0.62 IPS |
|
|
Object Detection (SP)
|
100% |
174
13.8 IPS |
|
|
Object Detection (HP)
|
100% |
170
13.5 IPS |
|
|
Object Detection (Q)
|
83% |
229
18.5 IPS |
|
|
Face Detection (SP)
|
100% |
343
4.07 IPS |
|
|
Face Detection (HP)
|
100% |
348
4.13 IPS |
|
|
Face Detection (Q)
|
95% |
542
6.47 IPS |
|
|
Depth Estimation (SP)
|
100% |
472
3.63 IPS |
|
|
Depth Estimation (HP)
|
99% |
456
3.51 IPS |
|
|
Depth Estimation (Q)
|
64% |
561
5.14 IPS |
|
|
Style Transfer (SP)
|
89% |
1200
1.56 IPS |
|
|
Style Transfer (HP)
|
89% |
1278
1.66 IPS |
|
|
Style Transfer (Q)
|
98% |
1401
1.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
274
10.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
272
10.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
288
10.7 IPS |
|
|
Text Classification (SP)
|
100% |
160
213.6 IPS |
|
|
Text Classification (HP)
|
100% |
166
221.4 IPS |
|
|
Text Classification (Q)
|
88% |
160
215.7 IPS |
|
|
Machine Translation (SP)
|
100% |
279
4.81 IPS |
|
|
Machine Translation (HP)
|
100% |
241
4.15 IPS |
|
|
Machine Translation (Q)
|
50% |
102
3.62 IPS |
