wishtel IRA_T1015
Geekbench AI Score
129
Single Precision Score
129
Half Precision Score
170
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 09 2024 02:16 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% |
55
10.2 IPS |
|
|
Image Classification (HP)
|
100% |
56
10.4 IPS |
|
|
Image Classification (Q)
|
100% |
113
21.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
70
1.13 IPS |
|
|
Image Segmentation (HP)
|
100% |
70
1.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
135
2.20 IPS |
|
|
Pose Estimation (SP)
|
100% |
278
0.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
279
0.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
204
0.24 IPS |
|
|
Object Detection (SP)
|
100% |
56
4.40 IPS |
|
|
Object Detection (HP)
|
100% |
56
4.40 IPS |
|
|
Object Detection (Q)
|
83% |
110
8.92 IPS |
|
|
Face Detection (SP)
|
100% |
189
2.25 IPS |
|
|
Face Detection (HP)
|
100% |
189
2.25 IPS |
|
|
Face Detection (Q)
|
95% |
306
3.65 IPS |
|
|
Depth Estimation (SP)
|
100% |
247
1.90 IPS |
|
|
Depth Estimation (HP)
|
99% |
250
1.93 IPS |
|
|
Depth Estimation (Q)
|
64% |
240
2.20 IPS |
|
|
Style Transfer (SP)
|
89% |
437
0.57 IPS |
|
|
Style Transfer (HP)
|
89% |
438
0.57 IPS |
|
|
Style Transfer (Q)
|
98% |
550
0.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
113
4.17 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
113
4.17 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
134
4.96 IPS |
|
|
Text Classification (SP)
|
100% |
70
93.8 IPS |
|
|
Text Classification (HP)
|
100% |
70
93.9 IPS |
|
|
Text Classification (Q)
|
88% |
116
156.8 IPS |
|
|
Machine Translation (SP)
|
100% |
134
2.31 IPS |
|
|
Machine Translation (HP)
|
100% |
132
2.28 IPS |
|
|
Machine Translation (Q)
|
50% |
98
3.49 IPS |
