OnePlus 9
Geekbench ML Score
660
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 09:38 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus 9 |
| Model ID | OnePlus LE2113 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 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 @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.11 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
296
55.4 IPS |
|
|
Image Classification (F16)
|
100% |
292
54.7 IPS |
|
|
Image Classification (I8)
|
97% |
657
123.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
375
6.26 IPS |
|
|
Image Segmentation (F16)
|
100% |
384
6.41 IPS |
|
|
Image Segmentation (I8)
|
98% |
487
8.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
717
0.87 IPS |
|
|
Pose Estimation (F16)
|
100% |
711
0.86 IPS |
|
|
Pose Estimation (I8)
|
100% |
3321
4.02 IPS |
|
|
Object Detection (F32)
|
100% |
325
24.3 IPS |
|
|
Object Detection (F16)
|
100% |
324
24.2 IPS |
|
|
Object Detection (I8)
|
61% |
851
63.5 IPS |
|
|
Face Detection (F32)
|
100% |
661
7.86 IPS |
|
|
Face Detection (F16)
|
100% |
684
8.14 IPS |
|
|
Face Detection (I8)
|
86% |
1849
22.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
725
5.62 IPS |
|
|
Depth Estimation (F16)
|
100% |
697
5.40 IPS |
|
|
Depth Estimation (I8)
|
95% |
1622
12.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1278
1.68 IPS |
|
|
Style Transfer (F16)
|
100% |
1335
1.76 IPS |
|
|
Style Transfer (I8)
|
98% |
2582
3.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
406
14.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
381
13.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1858
66.4 IPS |
|
|
Text Classification (F32)
|
100% |
398
572.2 IPS |
|
|
Text Classification (F16)
|
100% |
404
580.3 IPS |
|
|
Text Classification (I8)
|
92% |
297
426.4 IPS |
|
|
Machine Translation (F32)
|
100% |
747
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
775
14.3 IPS |
|
|
Machine Translation (I8)
|
64% |
276
5.08 IPS |
