OnePlus CPH2717
Geekbench ML Score
680
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 31 2025 12:46 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
476
89.2 IPS |
|
|
Image Classification (F16)
|
100% |
527
98.5 IPS |
|
|
Image Classification (I8)
|
97% |
343
64.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
869
14.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
992
16.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
967
16.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
650
0.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
914
1.11 IPS |
|
|
Pose Estimation (I8)
|
100% |
912
1.10 IPS |
|
|
Object Detection (F32)
|
100% |
297
22.2 IPS |
|
|
Object Detection (F16)
|
100% |
293
21.8 IPS |
|
|
Object Detection (I8)
|
62% |
294
22.0 IPS |
|
|
Face Detection (F32)
|
100% |
1307
15.5 IPS |
|
|
Face Detection (F16)
|
98% |
1390
16.5 IPS |
|
|
Face Detection (I8)
|
86% |
1346
16.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1123
8.71 IPS |
|
|
Depth Estimation (F16)
|
100% |
1346
10.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
1336
10.4 IPS |
|
|
Style Transfer (F32)
|
100% |
3412
4.49 IPS |
|
|
Style Transfer (F16)
|
100% |
4031
5.30 IPS |
|
|
Style Transfer (I8)
|
98% |
4041
5.32 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
608
21.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
668
23.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
688
24.6 IPS |
|
|
Text Classification (F32)
|
100% |
156
224.9 IPS |
|
|
Text Classification (F16)
|
100% |
161
231.5 IPS |
|
|
Text Classification (I8)
|
92% |
269
386.0 IPS |
|
|
Machine Translation (F32)
|
100% |
289
5.33 IPS |
|
|
Machine Translation (F16)
|
100% |
245
4.51 IPS |
|
|
Machine Translation (I8)
|
64% |
267
4.91 IPS |
