OnePlus OPD2415
Geekbench AI Score
736
Single Precision Score
743
Half Precision Score
920
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | fridriksa |
| Upload Date | February 24 2026 04:41 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OnePlus OPD2415 |
| Model ID | OnePlus OPD2415 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 15.07 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
336
62.4 IPS |
|
|
Image Classification (HP)
|
100% |
342
63.7 IPS |
|
|
Image Classification (Q)
|
99% |
1498
279.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
672
10.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
750
12.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
936
15.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2009
2.34 IPS |
|
|
Pose Estimation (HP)
|
92% |
3012
3.54 IPS |
|
|
Pose Estimation (Q)
|
96% |
4053
4.75 IPS |
|
|
Object Detection (SP)
|
98% |
1365
108.7 IPS |
|
|
Object Detection (HP)
|
97% |
409
32.5 IPS |
|
|
Object Detection (Q)
|
85% |
330
26.6 IPS |
|
|
Face Detection (SP)
|
100% |
1063
12.6 IPS |
|
|
Face Detection (HP)
|
100% |
1155
13.7 IPS |
|
|
Face Detection (Q)
|
97% |
1601
19.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
1001
7.74 IPS |
|
|
Depth Estimation (HP)
|
98% |
1212
9.37 IPS |
|
|
Depth Estimation (Q)
|
64% |
1353
12.5 IPS |
|
|
Style Transfer (SP)
|
89% |
4341
5.63 IPS |
|
|
Style Transfer (HP)
|
88% |
6437
8.36 IPS |
|
|
Style Transfer (Q)
|
98% |
7507
9.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
366
13.5 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
502
18.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2107
78.1 IPS |
|
|
Text Classification (SP)
|
100% |
278
371.5 IPS |
|
|
Text Classification (HP)
|
100% |
51
68.4 IPS |
|
|
Text Classification (Q)
|
93% |
52
70.2 IPS |
|
|
Machine Translation (SP)
|
100% |
162
2.79 IPS |
|
|
Machine Translation (HP)
|
96% |
712
12.3 IPS |
|
|
Machine Translation (Q)
|
55% |
131
3.52 IPS |
