OnePlus 9
Geekbench AI Score
1015
Single Precision Score
1012
Half Precision Score
1898
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Vicioxs2 |
| Upload Date | January 09 2026 06:06 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 888 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OnePlus 9 |
| Model ID | OnePlus LE2115 |
| Motherboard | lahaina |
| Governor | performance |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| 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 | 7.08 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
474
88.2 IPS |
|
|
Image Classification (HP)
|
100% |
496
92.2 IPS |
|
|
Image Classification (Q)
|
100% |
1481
275.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
588
9.53 IPS |
|
|
Image Segmentation (HP)
|
100% |
587
9.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
1693
27.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2162
2.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
2118
2.47 IPS |
|
|
Pose Estimation (Q)
|
84% |
3206
3.80 IPS |
|
|
Object Detection (SP)
|
100% |
458
36.3 IPS |
|
|
Object Detection (HP)
|
100% |
458
36.3 IPS |
|
|
Object Detection (Q)
|
83% |
1344
108.5 IPS |
|
|
Face Detection (SP)
|
100% |
1464
17.4 IPS |
|
|
Face Detection (HP)
|
100% |
1457
17.3 IPS |
|
|
Face Detection (Q)
|
95% |
3279
39.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1939
14.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1939
14.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3069
28.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3641
4.73 IPS |
|
|
Style Transfer (HP)
|
89% |
3533
4.59 IPS |
|
|
Style Transfer (Q)
|
98% |
7019
9.05 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1025
37.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1024
37.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1714
63.5 IPS |
|
|
Text Classification (SP)
|
100% |
505
674.1 IPS |
|
|
Text Classification (HP)
|
100% |
501
669.1 IPS |
|
|
Text Classification (Q)
|
88% |
850
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
790
13.6 IPS |
|
|
Machine Translation (HP)
|
100% |
784
13.5 IPS |
|
|
Machine Translation (Q)
|
50% |
546
19.4 IPS |
