AYANEO Pocket S2 Pro
Geekbench AI Score
2864
Single Precision Score
2889
Half Precision Score
4715
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | sunflower2333 |
| Upload Date | December 02 2025 06:36 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | AYANEO Pocket S2 Pro |
| Model ID | AYANEO Pocket S2 Pro |
| Motherboard | pineapple |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.92 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1837
341.6 IPS |
|
|
Image Classification (HP)
|
100% |
2427
451.4 IPS |
|
|
Image Classification (Q)
|
100% |
3491
649.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2723
44.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2691
43.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
4418
71.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4493
5.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
4335
5.06 IPS |
|
|
Pose Estimation (Q)
|
84% |
10117
12.0 IPS |
|
|
Object Detection (SP)
|
98% |
2160
171.9 IPS |
|
|
Object Detection (HP)
|
98% |
2125
169.1 IPS |
|
|
Object Detection (Q)
|
83% |
3407
275.2 IPS |
|
|
Face Detection (SP)
|
100% |
4280
50.9 IPS |
|
|
Face Detection (HP)
|
100% |
4178
49.6 IPS |
|
|
Face Detection (Q)
|
95% |
7389
88.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3843
29.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
3819
29.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
7474
68.5 IPS |
|
|
Style Transfer (SP)
|
89% |
10761
14.0 IPS |
|
|
Style Transfer (HP)
|
89% |
10429
13.5 IPS |
|
|
Style Transfer (Q)
|
98% |
20674
26.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2225
82.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2155
79.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5409
200.4 IPS |
|
|
Text Classification (SP)
|
100% |
1060
1.42 KIPS |
|
|
Text Classification (HP)
|
99% |
1059
1.41 KIPS |
|
|
Text Classification (Q)
|
88% |
1700
2.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
1836
31.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1775
30.6 IPS |
|
|
Machine Translation (Q)
|
50% |
975
34.6 IPS |
