Teclast ArtPadPro_ROW
Geekbench AI Score
285
Single Precision Score
476
Half Precision Score
392
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Oleksandr |
| Upload Date | December 16 2025 07:59 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Teclast ArtPadPro_ROW |
| Model ID | Teclast ArtPadPro_ROW |
| Motherboard | tb8781_64_cm89_v10 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.52 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
177
32.9 IPS |
|
|
Image Classification (HP)
|
100% |
315
58.6 IPS |
|
|
Image Classification (Q)
|
97% |
311
58.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
260
4.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
549
8.90 IPS |
|
|
Image Segmentation (Q)
|
98% |
489
7.95 IPS |
|
|
Pose Estimation (SP)
|
100% |
1158
1.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
2073
2.42 IPS |
|
|
Pose Estimation (Q)
|
95% |
2036
2.39 IPS |
|
|
Object Detection (SP)
|
100% |
160
12.7 IPS |
|
|
Object Detection (HP)
|
99% |
318
25.2 IPS |
|
|
Object Detection (Q)
|
83% |
312
25.2 IPS |
|
|
Face Detection (SP)
|
100% |
588
6.99 IPS |
|
|
Face Detection (HP)
|
100% |
1159
13.8 IPS |
|
|
Face Detection (Q)
|
96% |
980
11.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
813
6.26 IPS |
|
|
Depth Estimation (HP)
|
98% |
1520
11.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
1209
11.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1939
2.49 IPS |
|
|
Style Transfer (HP)
|
100% |
4074
5.24 IPS |
|
|
Style Transfer (Q)
|
98% |
3975
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
474
17.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
813
30.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
729
27.0 IPS |
|
|
Text Classification (SP)
|
35% |
6
56.1 IPS |
|
|
Text Classification (HP)
|
29% |
5
81.6 IPS |
|
|
Text Classification (Q)
|
32% |
6
80.0 IPS |
|
|
Machine Translation (SP)
|
100% |
161
2.77 IPS |
|
|
Machine Translation (HP)
|
100% |
182
3.13 IPS |
|
|
Machine Translation (Q)
|
43% |
44
2.57 IPS |
