OnePlus 9R
Geekbench ML Score
547
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 13 2024 08:56 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus 9R |
| Model ID | OnePlus LE2101 |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 7.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
257
48.1 IPS |
|
|
Image Classification (F16)
|
100% |
257
48.0 IPS |
|
|
Image Classification (I8)
|
97% |
570
106.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
372
6.21 IPS |
|
|
Image Segmentation (F16)
|
100% |
373
6.23 IPS |
|
|
Image Segmentation (I8)
|
98% |
489
8.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
571
0.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
571
0.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
2642
3.20 IPS |
|
|
Object Detection (F32)
|
100% |
306
22.8 IPS |
|
|
Object Detection (F16)
|
100% |
306
22.9 IPS |
|
|
Object Detection (I8)
|
61% |
794
59.3 IPS |
|
|
Face Detection (F32)
|
100% |
588
6.99 IPS |
|
|
Face Detection (F16)
|
100% |
594
7.07 IPS |
|
|
Face Detection (I8)
|
86% |
1491
17.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
572
4.44 IPS |
|
|
Depth Estimation (F16)
|
100% |
561
4.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
1402
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
941
1.24 IPS |
|
|
Style Transfer (F16)
|
100% |
887
1.17 IPS |
|
|
Style Transfer (I8)
|
98% |
2332
3.07 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
305
10.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
313
11.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1068
38.1 IPS |
|
|
Text Classification (F32)
|
100% |
285
409.1 IPS |
|
|
Text Classification (F16)
|
100% |
271
390.0 IPS |
|
|
Text Classification (I8)
|
92% |
232
333.2 IPS |
|
|
Machine Translation (F32)
|
100% |
634
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
625
11.5 IPS |
|
|
Machine Translation (I8)
|
64% |
266
4.89 IPS |
