Xiaomi Redmi Note 9 Pro
Geekbench AI Score
175
Single Precision Score
262
Half Precision Score
259
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | GladOS |
| Upload Date | January 29 2025 07:35 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 720G |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi Redmi Note 9 Pro |
| Model ID | Xiaomi Redmi Note 9 Pro |
| Motherboard | joyeuse |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 15 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.32 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
103
19.2 IPS |
|
|
Image Classification (HP)
|
100% |
163
30.3 IPS |
|
|
Image Classification (Q)
|
97% |
165
30.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
115
1.86 IPS |
|
|
Image Segmentation (HP)
|
100% |
193
3.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
169
2.74 IPS |
|
|
Pose Estimation (SP)
|
100% |
201
0.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
275
0.32 IPS |
|
|
Pose Estimation (Q)
|
95% |
275
0.32 IPS |
|
|
Object Detection (SP)
|
100% |
86
6.84 IPS |
|
|
Object Detection (HP)
|
100% |
125
9.88 IPS |
|
|
Object Detection (Q)
|
89% |
128
10.2 IPS |
|
|
Face Detection (SP)
|
100% |
229
2.73 IPS |
|
|
Face Detection (HP)
|
100% |
414
4.92 IPS |
|
|
Face Detection (Q)
|
97% |
406
4.84 IPS |
|
|
Depth Estimation (SP)
|
100% |
241
1.85 IPS |
|
|
Depth Estimation (HP)
|
99% |
404
3.12 IPS |
|
|
Depth Estimation (Q)
|
62% |
332
3.14 IPS |
|
|
Style Transfer (SP)
|
100% |
474
0.61 IPS |
|
|
Style Transfer (HP)
|
100% |
1010
1.30 IPS |
|
|
Style Transfer (Q)
|
98% |
1007
1.30 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
118
4.36 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
194
7.15 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
190
7.04 IPS |
|
|
Text Classification (SP)
|
100% |
162
216.7 IPS |
|
|
Text Classification (HP)
|
100% |
163
217.2 IPS |
|
|
Text Classification (Q)
|
91% |
270
363.5 IPS |
|
|
Machine Translation (SP)
|
100% |
266
4.58 IPS |
|
|
Machine Translation (HP)
|
100% |
269
4.64 IPS |
|
|
Machine Translation (Q)
|
57% |
205
5.01 IPS |
