Relndoo TAB9
Geekbench AI Score
206
Single Precision Score
210
Half Precision Score
290
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 22 2026 09:49 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Relndoo TAB9 |
| Model ID | Relndoo TAB9 |
| Motherboard | ums9230_6h10 |
| Governor | uscfreq |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.61 GHz |
| Cluster 1 | 6 Cores @ 1.61 GHz |
| Cluster 2 | 2 Cores @ 1.82 GHz |
| Memory Information | |
|---|---|
| Size | 3.77 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
92
17.1 IPS |
|
|
Image Classification (HP)
|
100% |
92
17.1 IPS |
|
|
Image Classification (Q)
|
100% |
196
36.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
117
1.89 IPS |
|
|
Image Segmentation (HP)
|
100% |
117
1.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
245
3.98 IPS |
|
|
Pose Estimation (SP)
|
100% |
472
0.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
473
0.55 IPS |
|
|
Pose Estimation (Q)
|
84% |
374
0.44 IPS |
|
|
Object Detection (SP)
|
100% |
92
7.32 IPS |
|
|
Object Detection (HP)
|
100% |
92
7.32 IPS |
|
|
Object Detection (Q)
|
83% |
190
15.3 IPS |
|
|
Face Detection (SP)
|
100% |
307
3.64 IPS |
|
|
Face Detection (HP)
|
100% |
306
3.64 IPS |
|
|
Face Detection (Q)
|
95% |
541
6.46 IPS |
|
|
Depth Estimation (SP)
|
100% |
286
2.20 IPS |
|
|
Depth Estimation (HP)
|
99% |
337
2.59 IPS |
|
|
Depth Estimation (Q)
|
64% |
426
3.91 IPS |
|
|
Style Transfer (SP)
|
89% |
775
1.01 IPS |
|
|
Style Transfer (HP)
|
89% |
773
1.00 IPS |
|
|
Style Transfer (Q)
|
98% |
966
1.25 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
203
7.49 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
210
7.77 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
235
8.72 IPS |
|
|
Text Classification (SP)
|
100% |
112
149.0 IPS |
|
|
Text Classification (HP)
|
100% |
111
148.2 IPS |
|
|
Text Classification (Q)
|
88% |
182
245.2 IPS |
|
|
Machine Translation (SP)
|
100% |
196
3.38 IPS |
|
|
Machine Translation (HP)
|
100% |
192
3.31 IPS |
|
|
Machine Translation (Q)
|
50% |
130
4.63 IPS |
