OnePlus CPH2419
Geekbench ML Score
705
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 02:53 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus CPH2419 |
| Model ID | OnePlus CPH2419 |
| 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% |
341
63.8 IPS |
|
|
Image Classification (F16)
|
100% |
334
62.5 IPS |
|
|
Image Classification (I8)
|
97% |
551
103.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
455
7.60 IPS |
|
|
Image Segmentation (F16)
|
100% |
469
7.83 IPS |
|
|
Image Segmentation (I8)
|
98% |
528
8.82 IPS |
|
|
Pose Estimation (F32)
|
100% |
840
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
826
1.00 IPS |
|
|
Pose Estimation (I8)
|
100% |
3128
3.79 IPS |
|
|
Object Detection (F32)
|
100% |
332
24.8 IPS |
|
|
Object Detection (F16)
|
100% |
346
25.8 IPS |
|
|
Object Detection (I8)
|
61% |
760
56.7 IPS |
|
|
Face Detection (F32)
|
100% |
757
9.00 IPS |
|
|
Face Detection (F16)
|
100% |
764
9.09 IPS |
|
|
Face Detection (I8)
|
86% |
1521
18.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
847
6.57 IPS |
|
|
Depth Estimation (F16)
|
100% |
845
6.56 IPS |
|
|
Depth Estimation (I8)
|
95% |
1726
13.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1576
2.07 IPS |
|
|
Style Transfer (F16)
|
100% |
1444
1.90 IPS |
|
|
Style Transfer (I8)
|
98% |
2903
3.82 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
477
17.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
499
17.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1414
50.5 IPS |
|
|
Text Classification (F32)
|
100% |
381
547.6 IPS |
|
|
Text Classification (F16)
|
100% |
390
560.2 IPS |
|
|
Text Classification (I8)
|
92% |
277
397.6 IPS |
|
|
Machine Translation (F32)
|
100% |
747
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
762
14.0 IPS |
|
|
Machine Translation (I8)
|
64% |
377
6.94 IPS |
