Teclast T65Max_ROW
Geekbench AI Score
453
Single Precision Score
477
Half Precision Score
914
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | oguogu |
| Upload Date | September 09 2024 11:28 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Teclast T65Max_ROW |
| Model ID | Teclast T65Max_ROW |
| Motherboard | MT6789 |
| 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 | 7.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
216
40.2 IPS |
|
|
Image Classification (HP)
|
100% |
216
40.2 IPS |
|
|
Image Classification (Q)
|
100% |
638
118.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
266
4.31 IPS |
|
|
Image Segmentation (HP)
|
100% |
266
4.31 IPS |
|
|
Image Segmentation (Q)
|
98% |
681
11.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1028
1.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
1034
1.21 IPS |
|
|
Pose Estimation (Q)
|
84% |
1605
1.90 IPS |
|
|
Object Detection (SP)
|
100% |
217
17.2 IPS |
|
|
Object Detection (HP)
|
100% |
217
17.2 IPS |
|
|
Object Detection (Q)
|
83% |
623
50.3 IPS |
|
|
Face Detection (SP)
|
100% |
642
7.62 IPS |
|
|
Face Detection (HP)
|
100% |
643
7.64 IPS |
|
|
Face Detection (Q)
|
95% |
1438
17.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
483
3.72 IPS |
|
|
Depth Estimation (HP)
|
99% |
841
6.48 IPS |
|
|
Depth Estimation (Q)
|
64% |
1467
13.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1764
2.29 IPS |
|
|
Style Transfer (HP)
|
89% |
1761
2.29 IPS |
|
|
Style Transfer (Q)
|
98% |
3659
4.72 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
450
16.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
445
16.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
881
32.6 IPS |
|
|
Text Classification (SP)
|
100% |
264
352.4 IPS |
|
|
Text Classification (HP)
|
100% |
263
350.4 IPS |
|
|
Text Classification (Q)
|
88% |
467
630.2 IPS |
|
|
Machine Translation (SP)
|
100% |
438
7.54 IPS |
|
|
Machine Translation (HP)
|
100% |
433
7.46 IPS |
|
|
Machine Translation (Q)
|
50% |
296
10.5 IPS |
