Xiaomi Redmi Note 14 5G Xiaomi 24094RAD4G
Geekbench AI Score
250
Single Precision Score
292
Half Precision Score
247
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Bxckam1422 |
| Upload Date | June 26 2025 10:45 AM |
| Views | 33 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi 24094RAD4G |
| Model ID | Xiaomi 24094RAD4G |
| Motherboard | citrine |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 7.33 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
188
35.0 IPS |
|
|
Image Classification (HP)
|
97% |
366
68.2 IPS |
|
|
Image Classification (Q)
|
97% |
102
19.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
252
4.09 IPS |
|
|
Image Segmentation (HP)
|
100% |
648
10.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
124
2.01 IPS |
|
|
Pose Estimation (SP)
|
99% |
1046
1.22 IPS |
|
|
Pose Estimation (HP)
|
98% |
2328
2.72 IPS |
|
|
Pose Estimation (Q)
|
70% |
1271
1.62 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
367
29.1 IPS |
|
|
Object Detection (Q)
|
80% |
119
9.70 IPS |
|
|
Face Detection (SP)
|
100% |
618
7.34 IPS |
|
|
Face Detection (HP)
|
100% |
1206
14.3 IPS |
|
|
Face Detection (Q)
|
97% |
185
2.21 IPS |
|
|
Depth Estimation (SP)
|
84% |
683
5.35 IPS |
|
|
Depth Estimation (HP)
|
84% |
1638
12.8 IPS |
|
|
Depth Estimation (Q)
|
57% |
288
3.14 IPS |
|
|
Style Transfer (SP)
|
100% |
903
1.16 IPS |
|
|
Style Transfer (HP)
|
100% |
367
0.47 IPS |
|
|
Style Transfer (Q)
|
98% |
1733
2.23 IPS |
|
|
Image Super-Resolution (SP)
|
98% |
463
17.2 IPS |
|
|
Image Super-Resolution (HP)
|
0
|
||
|
Image Super-Resolution (Q)
|
97% |
456
16.9 IPS |
|
|
Text Classification (SP)
|
29% |
4
65.9 IPS |
|
|
Text Classification (HP)
|
100% |
132
176.7 IPS |
|
|
Text Classification (Q)
|
93% |
96
129.1 IPS |
|
|
Machine Translation (SP)
|
100% |
161
2.78 IPS |
|
|
Machine Translation (HP)
|
100% |
234
4.03 IPS |
|
|
Machine Translation (Q)
|
55% |
113
2.99 IPS |
