OnePlus 10T
Geekbench ML Score
671
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:51 PM |
| Views | 1 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
320
59.9 IPS |
|
|
Image Classification (F16)
|
100% |
334
62.5 IPS |
|
|
Image Classification (I8)
|
97% |
552
103.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
448
7.48 IPS |
|
|
Image Segmentation (F16)
|
100% |
440
7.35 IPS |
|
|
Image Segmentation (I8)
|
98% |
472
7.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
847
1.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
853
1.03 IPS |
|
|
Pose Estimation (I8)
|
100% |
3216
3.89 IPS |
|
|
Object Detection (F32)
|
100% |
342
25.6 IPS |
|
|
Object Detection (F16)
|
100% |
343
25.6 IPS |
|
|
Object Detection (I8)
|
61% |
717
53.6 IPS |
|
|
Face Detection (F32)
|
100% |
795
9.46 IPS |
|
|
Face Detection (F16)
|
100% |
619
7.35 IPS |
|
|
Face Detection (I8)
|
86% |
1538
18.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
840
6.52 IPS |
|
|
Depth Estimation (F16)
|
100% |
841
6.52 IPS |
|
|
Depth Estimation (I8)
|
95% |
1580
12.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1564
2.06 IPS |
|
|
Style Transfer (F16)
|
100% |
1427
1.88 IPS |
|
|
Style Transfer (I8)
|
98% |
2733
3.60 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
488
17.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
442
15.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1174
41.9 IPS |
|
|
Text Classification (F32)
|
100% |
379
545.3 IPS |
|
|
Text Classification (F16)
|
100% |
384
552.1 IPS |
|
|
Text Classification (I8)
|
92% |
295
424.5 IPS |
|
|
Machine Translation (F32)
|
100% |
448
8.25 IPS |
|
|
Machine Translation (F16)
|
100% |
648
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
373
6.86 IPS |
