OnePlus 9R
Geekbench ML Score
611
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 13 2024 09:00 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
291
54.5 IPS |
|
|
Image Classification (F16)
|
100% |
433
81.1 IPS |
|
|
Image Classification (I8)
|
97% |
442
82.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
362
6.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
677
11.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
673
11.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
540
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
1085
1.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
1084
1.31 IPS |
|
|
Object Detection (F32)
|
100% |
205
15.3 IPS |
|
|
Object Detection (F16)
|
100% |
370
27.6 IPS |
|
|
Object Detection (I8)
|
62% |
231
17.2 IPS |
|
|
Face Detection (F32)
|
100% |
707
8.41 IPS |
|
|
Face Detection (F16)
|
97% |
1478
17.6 IPS |
|
|
Face Detection (I8)
|
87% |
1351
16.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
594
4.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
1071
8.30 IPS |
|
|
Depth Estimation (I8)
|
95% |
1057
8.20 IPS |
|
|
Style Transfer (F32)
|
100% |
1250
1.64 IPS |
|
|
Style Transfer (F16)
|
100% |
3206
4.22 IPS |
|
|
Style Transfer (I8)
|
98% |
3227
4.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
331
11.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
763
27.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
745
26.6 IPS |
|
|
Text Classification (F32)
|
100% |
232
333.8 IPS |
|
|
Text Classification (F16)
|
100% |
234
336.1 IPS |
|
|
Text Classification (I8)
|
92% |
405
581.4 IPS |
|
|
Machine Translation (F32)
|
100% |
389
7.16 IPS |
|
|
Machine Translation (F16)
|
100% |
391
7.20 IPS |
|
|
Machine Translation (I8)
|
64% |
495
9.10 IPS |
