Phone - Xiaomi Redmi Note 8T Xiaomi Redmi Note 8T
Geekbench AI Score
307
Single Precision Score
301
Half Precision Score
310
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | kecskesajt |
| Upload Date | December 03 2024 04:39 PM |
| Views | 10 |
| Notes | Qualcomm Snapdragon 665 Adreno 610 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Redmi Note 8T |
| Model ID | Xiaomi Redmi Note 8T |
| Motherboard | trinket |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 3.56 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
157
29.3 IPS |
|
|
Image Classification (HP)
|
100% |
152
28.3 IPS |
|
|
Image Classification (Q)
|
100% |
212
39.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
187
3.03 IPS |
|
|
Image Segmentation (HP)
|
100% |
171
2.78 IPS |
|
|
Image Segmentation (Q)
|
98% |
296
4.81 IPS |
|
|
Pose Estimation (SP)
|
100% |
659
0.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
645
0.75 IPS |
|
|
Pose Estimation (Q)
|
84% |
474
0.56 IPS |
|
|
Object Detection (SP)
|
100% |
164
13.0 IPS |
|
|
Object Detection (HP)
|
100% |
161
12.8 IPS |
|
|
Object Detection (Q)
|
83% |
217
17.5 IPS |
|
|
Face Detection (SP)
|
100% |
380
4.51 IPS |
|
|
Face Detection (HP)
|
100% |
374
4.44 IPS |
|
|
Face Detection (Q)
|
95% |
547
6.54 IPS |
|
|
Depth Estimation (SP)
|
100% |
485
3.74 IPS |
|
|
Depth Estimation (HP)
|
99% |
469
3.61 IPS |
|
|
Depth Estimation (Q)
|
64% |
531
4.87 IPS |
|
|
Style Transfer (SP)
|
89% |
1204
1.56 IPS |
|
|
Style Transfer (HP)
|
89% |
1207
1.57 IPS |
|
|
Style Transfer (Q)
|
98% |
1290
1.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
257
9.51 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
262
9.68 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
265
9.84 IPS |
|
|
Text Classification (SP)
|
100% |
162
216.0 IPS |
|
|
Text Classification (HP)
|
100% |
160
214.2 IPS |
|
|
Text Classification (Q)
|
88% |
143
192.8 IPS |
|
|
Machine Translation (SP)
|
100% |
254
4.37 IPS |
|
|
Machine Translation (HP)
|
100% |
255
4.38 IPS |
|
|
Machine Translation (Q)
|
50% |
92
3.27 IPS |
