OnePlus CPH2491
Geekbench ML Score
816
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 03:31 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | OnePlus CPH2491 |
| Model ID | OnePlus CPH2491 |
| Motherboard | k6983v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.05 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
477
89.3 IPS |
|
|
Image Classification (F16)
|
100% |
690
129.1 IPS |
|
|
Image Classification (I8)
|
97% |
582
108.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
778
13.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
992
16.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
982
16.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
607
0.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
882
1.07 IPS |
|
|
Pose Estimation (I8)
|
100% |
877
1.06 IPS |
|
|
Object Detection (F32)
|
100% |
392
29.3 IPS |
|
|
Object Detection (F16)
|
100% |
554
41.4 IPS |
|
|
Object Detection (I8)
|
62% |
559
41.7 IPS |
|
|
Face Detection (F32)
|
100% |
1762
20.9 IPS |
|
|
Face Detection (F16)
|
98% |
2308
27.4 IPS |
|
|
Face Detection (I8)
|
86% |
2121
25.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
962
7.46 IPS |
|
|
Depth Estimation (F16)
|
100% |
1130
8.77 IPS |
|
|
Depth Estimation (I8)
|
95% |
1121
8.69 IPS |
|
|
Style Transfer (F32)
|
100% |
2563
3.37 IPS |
|
|
Style Transfer (F16)
|
100% |
3543
4.66 IPS |
|
|
Style Transfer (I8)
|
98% |
3500
4.60 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
532
19.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
706
25.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
701
25.0 IPS |
|
|
Text Classification (F32)
|
100% |
263
378.3 IPS |
|
|
Text Classification (F16)
|
100% |
266
382.3 IPS |
|
|
Text Classification (I8)
|
92% |
493
707.9 IPS |
|
|
Machine Translation (F32)
|
100% |
413
7.60 IPS |
|
|
Machine Translation (F16)
|
100% |
422
7.76 IPS |
|
|
Machine Translation (I8)
|
64% |
515
9.48 IPS |
