Xiaomi Redmi Note 8
Geekbench AI Score
313
Single Precision Score
313
Half Precision Score
329
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 13 2025 06:16 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 665 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
161
29.9 IPS |
|
|
Image Classification (HP)
|
100% |
159
29.6 IPS |
|
|
Image Classification (Q)
|
100% |
203
37.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
195
3.17 IPS |
|
|
Image Segmentation (HP)
|
100% |
195
3.16 IPS |
|
|
Image Segmentation (Q)
|
98% |
300
4.87 IPS |
|
|
Pose Estimation (SP)
|
100% |
691
0.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
696
0.81 IPS |
|
|
Pose Estimation (Q)
|
84% |
494
0.59 IPS |
|
|
Object Detection (SP)
|
100% |
158
12.5 IPS |
|
|
Object Detection (HP)
|
100% |
167
13.3 IPS |
|
|
Object Detection (Q)
|
83% |
221
17.8 IPS |
|
|
Face Detection (SP)
|
100% |
371
4.41 IPS |
|
|
Face Detection (HP)
|
100% |
368
4.37 IPS |
|
|
Face Detection (Q)
|
95% |
565
6.75 IPS |
|
|
Depth Estimation (SP)
|
100% |
505
3.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
440
3.39 IPS |
|
|
Depth Estimation (Q)
|
64% |
531
4.87 IPS |
|
|
Style Transfer (SP)
|
89% |
1281
1.66 IPS |
|
|
Style Transfer (HP)
|
89% |
1287
1.67 IPS |
|
|
Style Transfer (Q)
|
98% |
1318
1.70 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
272
10.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
279
10.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
272
10.1 IPS |
|
|
Text Classification (SP)
|
100% |
156
208.7 IPS |
|
|
Text Classification (HP)
|
100% |
170
226.5 IPS |
|
|
Text Classification (Q)
|
88% |
192
258.5 IPS |
|
|
Machine Translation (SP)
|
100% |
259
4.47 IPS |
|
|
Machine Translation (HP)
|
100% |
258
4.44 IPS |
|
|
Machine Translation (Q)
|
50% |
111
3.93 IPS |
