Xiaomi Redmi Note 9 Pro
Geekbench AI Score
179
Single Precision Score
288
Half Precision Score
297
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | hafizsyawaldi |
| Upload Date | September 01 2024 05:51 AM |
| Views | 38 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi Note 9 Pro |
| Model ID | Xiaomi Redmi Note 9 Pro |
| Motherboard | atoll |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
107
20.0 IPS |
|
|
Image Classification (HP)
|
100% |
184
34.2 IPS |
|
|
Image Classification (Q)
|
99% |
189
35.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
131
2.13 IPS |
|
|
Image Segmentation (HP)
|
100% |
272
4.41 IPS |
|
|
Image Segmentation (Q)
|
98% |
274
4.45 IPS |
|
|
Pose Estimation (SP)
|
100% |
199
0.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
249
0.29 IPS |
|
|
Pose Estimation (Q)
|
96% |
247
0.29 IPS |
|
|
Object Detection (SP)
|
100% |
96
7.63 IPS |
|
|
Object Detection (HP)
|
100% |
146
11.6 IPS |
|
|
Object Detection (Q)
|
89% |
157
12.6 IPS |
|
|
Face Detection (SP)
|
100% |
241
2.87 IPS |
|
|
Face Detection (HP)
|
100% |
534
6.34 IPS |
|
|
Face Detection (Q)
|
97% |
561
6.69 IPS |
|
|
Depth Estimation (SP)
|
100% |
226
1.74 IPS |
|
|
Depth Estimation (HP)
|
99% |
422
3.25 IPS |
|
|
Depth Estimation (Q)
|
74% |
400
3.26 IPS |
|
|
Style Transfer (SP)
|
100% |
451
0.58 IPS |
|
|
Style Transfer (HP)
|
100% |
988
1.27 IPS |
|
|
Style Transfer (Q)
|
98% |
981
1.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
115
4.23 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
220
8.13 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
218
8.08 IPS |
|
|
Text Classification (SP)
|
100% |
163
218.0 IPS |
|
|
Text Classification (HP)
|
100% |
165
220.4 IPS |
|
|
Text Classification (Q)
|
91% |
274
367.7 IPS |
|
|
Machine Translation (SP)
|
100% |
275
4.73 IPS |
|
|
Machine Translation (HP)
|
100% |
274
4.72 IPS |
|
|
Machine Translation (Q)
|
57% |
205
5.02 IPS |
