Xiaomi Redmi Note 8 Pro
Geekbench AI Score
439
Single Precision Score
440
Half Precision Score
811
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Whiteyu |
| Upload Date | February 04 2026 05:47 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Mediatek Helio G90T |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Xiaomi Redmi Note 8 Pro |
| Model ID | Xiaomi Redmi Note 8 Pro |
| Motherboard | begonia |
| CPU Information | |
|---|---|
| Name | ARM MT6785V/CC |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.05 GHz |
| Memory Information | |
|---|---|
| Size | 5.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
203
37.8 IPS |
|
|
Image Classification (HP)
|
100% |
197
36.7 IPS |
|
|
Image Classification (Q)
|
100% |
549
102.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
250
4.05 IPS |
|
|
Image Segmentation (HP)
|
100% |
247
4.00 IPS |
|
|
Image Segmentation (Q)
|
98% |
622
10.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
966
1.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
951
1.11 IPS |
|
|
Pose Estimation (Q)
|
84% |
1346
1.60 IPS |
|
|
Object Detection (SP)
|
100% |
194
15.4 IPS |
|
|
Object Detection (HP)
|
100% |
201
16.0 IPS |
|
|
Object Detection (Q)
|
83% |
546
44.1 IPS |
|
|
Face Detection (SP)
|
100% |
645
7.67 IPS |
|
|
Face Detection (HP)
|
100% |
642
7.62 IPS |
|
|
Face Detection (Q)
|
95% |
1076
12.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
658
5.07 IPS |
|
|
Depth Estimation (HP)
|
99% |
759
5.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
1353
12.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1589
2.06 IPS |
|
|
Style Transfer (HP)
|
89% |
1572
2.04 IPS |
|
|
Style Transfer (Q)
|
98% |
3262
4.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
428
15.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
408
15.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
765
28.4 IPS |
|
|
Text Classification (SP)
|
100% |
238
317.0 IPS |
|
|
Text Classification (HP)
|
100% |
236
314.9 IPS |
|
|
Text Classification (Q)
|
88% |
445
599.6 IPS |
|
|
Machine Translation (SP)
|
100% |
407
7.00 IPS |
|
|
Machine Translation (HP)
|
100% |
405
6.97 IPS |
|
|
Machine Translation (Q)
|
50% |
305
10.8 IPS |
