Xiaomi Redmi Note 12 Turbo
Geekbench AI Score
549
Single Precision Score
788
Half Precision Score
781
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 27 2024 10:30 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 7+ Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi Note 12 Turbo |
| Model ID | Xiaomi 23049RAD8C |
| Motherboard | marble |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 2.92 GHz |
| Memory Information | |
|---|---|
| Size | 7.01 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
370
68.7 IPS |
|
|
Image Classification (HP)
|
100% |
362
67.3 IPS |
|
|
Image Classification (Q)
|
97% |
337
62.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
748
12.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1314
21.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
1097
17.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
595
0.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
1088
1.27 IPS |
|
|
Pose Estimation (Q)
|
95% |
1097
1.29 IPS |
|
|
Object Detection (SP)
|
100% |
300
23.8 IPS |
|
|
Object Detection (HP)
|
100% |
513
40.7 IPS |
|
|
Object Detection (Q)
|
89% |
515
41.2 IPS |
|
|
Face Detection (SP)
|
100% |
1253
14.9 IPS |
|
|
Face Detection (HP)
|
100% |
1523
18.1 IPS |
|
|
Face Detection (Q)
|
97% |
1435
17.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
904
6.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
1634
12.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
1305
12.3 IPS |
|
|
Style Transfer (SP)
|
100% |
2000
2.57 IPS |
|
|
Style Transfer (HP)
|
100% |
4387
5.64 IPS |
|
|
Style Transfer (Q)
|
98% |
4319
5.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
327
12.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
466
17.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
455
16.8 IPS |
|
|
Text Classification (SP)
|
100% |
200
266.5 IPS |
|
|
Text Classification (HP)
|
100% |
200
267.3 IPS |
|
|
Text Classification (Q)
|
91% |
356
478.6 IPS |
|
|
Machine Translation (SP)
|
100% |
344
5.92 IPS |
|
|
Machine Translation (HP)
|
100% |
343
5.92 IPS |
|
|
Machine Translation (Q)
|
57% |
310
7.56 IPS |
