OnePlus CPH2717
Geekbench ML Score
545
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 31 2025 12:42 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OnePlus CPH2717 |
| Model ID | OnePlus CPH2717 |
| Motherboard | k6897v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 7.30 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
310
58.0 IPS |
|
|
Image Classification (F16)
|
100% |
298
55.7 IPS |
|
|
Image Classification (I8)
|
97% |
375
70.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
362
6.05 IPS |
|
|
Image Segmentation (F16)
|
100% |
364
6.07 IPS |
|
|
Image Segmentation (I8)
|
98% |
430
7.19 IPS |
|
|
Pose Estimation (F32)
|
100% |
693
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
695
0.84 IPS |
|
|
Pose Estimation (I8)
|
100% |
2680
3.25 IPS |
|
|
Object Detection (F32)
|
100% |
269
20.1 IPS |
|
|
Object Detection (F16)
|
100% |
277
20.6 IPS |
|
|
Object Detection (I8)
|
61% |
453
33.8 IPS |
|
|
Face Detection (F32)
|
100% |
680
8.09 IPS |
|
|
Face Detection (F16)
|
100% |
672
7.99 IPS |
|
|
Face Detection (I8)
|
86% |
917
10.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
668
5.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
672
5.21 IPS |
|
|
Depth Estimation (I8)
|
95% |
1005
7.80 IPS |
|
|
Style Transfer (F32)
|
100% |
1371
1.80 IPS |
|
|
Style Transfer (F16)
|
100% |
1354
1.78 IPS |
|
|
Style Transfer (I8)
|
98% |
3180
4.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
243
8.66 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
405
14.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1025
36.6 IPS |
|
|
Text Classification (F32)
|
100% |
311
446.7 IPS |
|
|
Text Classification (F16)
|
100% |
311
446.5 IPS |
|
|
Text Classification (I8)
|
92% |
239
343.6 IPS |
|
|
Machine Translation (F32)
|
100% |
523
9.63 IPS |
|
|
Machine Translation (F16)
|
100% |
522
9.61 IPS |
|
|
Machine Translation (I8)
|
64% |
211
3.88 IPS |
