OnePlus 10T
Geekbench ML Score
307
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 05:01 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus 10T |
| Model ID | OnePlus CPH2415 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 4 Cores @ 2.02 GHz |
| Cluster 2 | 3 Cores @ 2.75 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
125
23.4 IPS |
|
|
Image Classification (F16)
|
100% |
129
24.1 IPS |
|
|
Image Classification (I8)
|
97% |
349
65.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
163
2.73 IPS |
|
|
Image Segmentation (F16)
|
100% |
172
2.86 IPS |
|
|
Image Segmentation (I8)
|
98% |
363
6.06 IPS |
|
|
Pose Estimation (F32)
|
100% |
226
0.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
228
0.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
899
1.09 IPS |
|
|
Object Detection (F32)
|
100% |
133
9.94 IPS |
|
|
Object Detection (F16)
|
100% |
138
10.3 IPS |
|
|
Object Detection (I8)
|
61% |
468
34.9 IPS |
|
|
Face Detection (F32)
|
100% |
364
4.32 IPS |
|
|
Face Detection (F16)
|
100% |
369
4.39 IPS |
|
|
Face Detection (I8)
|
86% |
833
9.91 IPS |
|
|
Depth Estimation (F32)
|
100% |
298
2.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
298
2.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
837
6.49 IPS |
|
|
Style Transfer (F32)
|
100% |
515
0.68 IPS |
|
|
Style Transfer (F16)
|
100% |
528
0.69 IPS |
|
|
Style Transfer (I8)
|
98% |
1386
1.82 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
168
5.99 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
147
5.25 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
533
19.0 IPS |
|
|
Text Classification (F32)
|
100% |
180
258.3 IPS |
|
|
Text Classification (F16)
|
100% |
168
241.6 IPS |
|
|
Text Classification (I8)
|
92% |
365
524.2 IPS |
|
|
Machine Translation (F32)
|
100% |
331
6.09 IPS |
|
|
Machine Translation (F16)
|
100% |
329
6.05 IPS |
|
|
Machine Translation (I8)
|
64% |
399
7.34 IPS |
