CUBOT Tab S9
Geekbench AI Score
332
Single Precision Score
340
Half Precision Score
377
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 17 2025 10:48 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT8183 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | CUBOT Tab S9 |
| Model ID | CUBOT Tab S9 |
| Motherboard | CUBOT |
| CPU Information | |
|---|---|
| Name | ARM MT8183 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.99 GHz |
| Cluster 1 | 8 Cores @ 1.99 GHz |
| Memory Information | |
|---|---|
| Size | 5.70 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
128
23.8 IPS |
|
|
Image Classification (HP)
|
100% |
168
31.3 IPS |
|
|
Image Classification (Q)
|
100% |
262
48.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
201
3.26 IPS |
|
|
Image Segmentation (HP)
|
100% |
207
3.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
323
5.25 IPS |
|
|
Pose Estimation (SP)
|
100% |
784
0.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
757
0.88 IPS |
|
|
Pose Estimation (Q)
|
84% |
585
0.69 IPS |
|
|
Object Detection (SP)
|
100% |
181
14.4 IPS |
|
|
Object Detection (HP)
|
100% |
177
14.0 IPS |
|
|
Object Detection (Q)
|
83% |
258
20.9 IPS |
|
|
Face Detection (SP)
|
100% |
413
4.91 IPS |
|
|
Face Detection (HP)
|
100% |
419
4.98 IPS |
|
|
Face Detection (Q)
|
95% |
611
7.30 IPS |
|
|
Depth Estimation (SP)
|
100% |
539
4.15 IPS |
|
|
Depth Estimation (HP)
|
99% |
545
4.20 IPS |
|
|
Depth Estimation (Q)
|
64% |
598
5.48 IPS |
|
|
Style Transfer (SP)
|
89% |
1411
1.83 IPS |
|
|
Style Transfer (HP)
|
89% |
1418
1.84 IPS |
|
|
Style Transfer (Q)
|
98% |
1604
2.07 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
294
10.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
288
10.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
347
12.9 IPS |
|
|
Text Classification (SP)
|
100% |
174
232.6 IPS |
|
|
Text Classification (HP)
|
100% |
174
231.7 IPS |
|
|
Text Classification (Q)
|
88% |
190
256.9 IPS |
|
|
Machine Translation (SP)
|
100% |
279
4.80 IPS |
|
|
Machine Translation (HP)
|
100% |
277
4.77 IPS |
|
|
Machine Translation (Q)
|
50% |
119
4.21 IPS |
