Xiaomi Redmi K40
Geekbench AI Score
231
Single Precision Score
229
Half Precision Score
1000
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | kitsunechan_2525 |
| Upload Date | June 08 2025 12:28 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 870 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi K40 |
| Model ID | Xiaomi M2012K11AC |
| Motherboard | alioth |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 7.34 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
148
27.5 IPS |
|
|
Image Classification (HP)
|
100% |
151
28.1 IPS |
|
|
Image Classification (Q)
|
96% |
1194
222.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
192
3.12 IPS |
|
|
Image Segmentation (HP)
|
100% |
195
3.15 IPS |
|
|
Image Segmentation (Q)
|
98% |
1263
20.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
247
0.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
232
0.27 IPS |
|
|
Pose Estimation (Q)
|
96% |
13335
15.6 IPS |
|
|
Object Detection (SP)
|
100% |
133
10.6 IPS |
|
|
Object Detection (HP)
|
100% |
134
10.6 IPS |
|
|
Object Detection (Q)
|
84% |
1324
106.8 IPS |
|
|
Face Detection (SP)
|
100% |
348
4.14 IPS |
|
|
Face Detection (HP)
|
100% |
332
3.94 IPS |
|
|
Face Detection (Q)
|
97% |
2166
25.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
290
2.23 IPS |
|
|
Depth Estimation (HP)
|
99% |
281
2.17 IPS |
|
|
Depth Estimation (Q)
|
64% |
5576
51.3 IPS |
|
|
Style Transfer (SP)
|
100% |
465
0.60 IPS |
|
|
Style Transfer (HP)
|
100% |
465
0.60 IPS |
|
|
Style Transfer (Q)
|
98% |
18850
24.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
140
5.15 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
140
5.16 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
513
19.0 IPS |
|
|
Text Classification (SP)
|
100% |
205
273.9 IPS |
|
|
Text Classification (HP)
|
100% |
222
296.0 IPS |
|
|
Text Classification (Q)
|
93% |
324
434.8 IPS |
|
|
Machine Translation (SP)
|
100% |
347
5.98 IPS |
|
|
Machine Translation (HP)
|
100% |
324
5.58 IPS |
|
|
Machine Translation (Q)
|
0% |
0
2.09 IPS |
