wishtel IRA_T1015
Geekbench AI Score
131
Single Precision Score
131
Half Precision Score
170
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 19 2024 10:52 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | wishtel IRA_T1015 |
| Model ID | wishtel IRA_T1015 |
| Motherboard | ums312_2h10 |
| Governor | uscfreq |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 3 Cores @ 1.82 GHz |
| Cluster 2 | 1 Core @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.73 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
56
10.3 IPS |
|
|
Image Classification (HP)
|
100% |
56
10.4 IPS |
|
|
Image Classification (Q)
|
100% |
112
20.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
70
1.14 IPS |
|
|
Image Segmentation (HP)
|
100% |
70
1.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
136
2.21 IPS |
|
|
Pose Estimation (SP)
|
100% |
278
0.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
279
0.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
203
0.24 IPS |
|
|
Object Detection (SP)
|
100% |
55
4.36 IPS |
|
|
Object Detection (HP)
|
100% |
55
4.40 IPS |
|
|
Object Detection (Q)
|
83% |
110
8.92 IPS |
|
|
Face Detection (SP)
|
100% |
187
2.23 IPS |
|
|
Face Detection (HP)
|
100% |
187
2.23 IPS |
|
|
Face Detection (Q)
|
95% |
305
3.64 IPS |
|
|
Depth Estimation (SP)
|
100% |
253
1.95 IPS |
|
|
Depth Estimation (HP)
|
99% |
243
1.87 IPS |
|
|
Depth Estimation (Q)
|
64% |
240
2.19 IPS |
|
|
Style Transfer (SP)
|
89% |
449
0.58 IPS |
|
|
Style Transfer (HP)
|
89% |
450
0.58 IPS |
|
|
Style Transfer (Q)
|
98% |
550
0.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
134
4.95 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
136
5.00 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
134
4.96 IPS |
|
|
Text Classification (SP)
|
100% |
70
93.5 IPS |
|
|
Text Classification (HP)
|
100% |
70
93.5 IPS |
|
|
Text Classification (Q)
|
88% |
115
155.2 IPS |
|
|
Machine Translation (SP)
|
100% |
134
2.30 IPS |
|
|
Machine Translation (HP)
|
100% |
133
2.29 IPS |
|
|
Machine Translation (Q)
|
50% |
98
3.48 IPS |
