OnePlus 5T
Geekbench AI Score
159
Single Precision Score
281
Half Precision Score
270
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | CME |
| Upload Date | August 15 2024 06:57 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 835 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus 5T |
| Model ID | OnePlus ONEPLUS A5010 |
| Motherboard | msm8998 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 1 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.46 GHz |
| Memory Information | |
|---|---|
| Size | 7.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
140
26.0 IPS |
|
|
Image Classification (HP)
|
100% |
271
50.4 IPS |
|
|
Image Classification (Q)
|
97% |
262
48.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
208
3.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
291
4.72 IPS |
|
|
Image Segmentation (Q)
|
98% |
280
4.55 IPS |
|
|
Pose Estimation (SP)
|
100% |
155
0.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
396
0.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
363
0.43 IPS |
|
|
Object Detection (SP)
|
100% |
92
7.28 IPS |
|
|
Object Detection (HP)
|
100% |
157
12.4 IPS |
|
|
Object Detection (Q)
|
86% |
151
12.1 IPS |
|
|
Face Detection (SP)
|
100% |
367
4.37 IPS |
|
|
Face Detection (HP)
|
100% |
610
7.25 IPS |
|
|
Face Detection (Q)
|
97% |
579
6.91 IPS |
|
|
Depth Estimation (SP)
|
100% |
211
1.63 IPS |
|
|
Depth Estimation (HP)
|
99% |
464
3.58 IPS |
|
|
Depth Estimation (Q)
|
75% |
445
3.60 IPS |
|
|
Style Transfer (SP)
|
100% |
423
0.54 IPS |
|
|
Style Transfer (HP)
|
100% |
1098
1.41 IPS |
|
|
Style Transfer (Q)
|
98% |
1089
1.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
87
3.22 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
228
8.40 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
225
8.33 IPS |
|
|
Text Classification (SP)
|
100% |
72
96.0 IPS |
|
|
Text Classification (HP)
|
100% |
72
95.7 IPS |
|
|
Text Classification (Q)
|
91% |
93
125.2 IPS |
|
|
Machine Translation (SP)
|
100% |
126
2.16 IPS |
|
|
Machine Translation (HP)
|
100% |
125
2.16 IPS |
|
|
Machine Translation (Q)
|
57% |
89
2.19 IPS |
