OnePlus 10T
Geekbench ML Score
708
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 27 2024 01:45 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus 10T |
| Model ID | OnePlus CPH2413 |
| 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 | 14.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
336
62.8 IPS |
|
|
Image Classification (F16)
|
100% |
341
63.8 IPS |
|
|
Image Classification (I8)
|
97% |
596
111.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
452
7.56 IPS |
|
|
Image Segmentation (F16)
|
100% |
464
7.75 IPS |
|
|
Image Segmentation (I8)
|
98% |
562
9.39 IPS |
|
|
Pose Estimation (F32)
|
100% |
868
1.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
872
1.06 IPS |
|
|
Pose Estimation (I8)
|
100% |
3530
4.27 IPS |
|
|
Object Detection (F32)
|
100% |
340
25.4 IPS |
|
|
Object Detection (F16)
|
100% |
345
25.7 IPS |
|
|
Object Detection (I8)
|
61% |
725
54.1 IPS |
|
|
Face Detection (F32)
|
100% |
834
9.91 IPS |
|
|
Face Detection (F16)
|
100% |
799
9.50 IPS |
|
|
Face Detection (I8)
|
86% |
1273
15.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
846
6.56 IPS |
|
|
Depth Estimation (F16)
|
100% |
866
6.71 IPS |
|
|
Depth Estimation (I8)
|
95% |
1613
12.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1549
2.04 IPS |
|
|
Style Transfer (F16)
|
100% |
1605
2.11 IPS |
|
|
Style Transfer (I8)
|
98% |
3016
3.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
485
17.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
484
17.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1254
44.8 IPS |
|
|
Text Classification (F32)
|
100% |
340
489.0 IPS |
|
|
Text Classification (F16)
|
100% |
365
525.2 IPS |
|
|
Text Classification (I8)
|
92% |
275
395.1 IPS |
|
|
Machine Translation (F32)
|
100% |
774
14.2 IPS |
|
|
Machine Translation (F16)
|
100% |
764
14.1 IPS |
|
|
Machine Translation (I8)
|
64% |
396
7.30 IPS |
