Coosea SN509A
Geekbench AI Score
445
Single Precision Score
433
Half Precision Score
872
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 02 2025 09:16 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Coosea SN509A |
| Model ID | Coosea SN509A |
| Motherboard | SN509A |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 5.53 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
211
39.3 IPS |
|
|
Image Classification (HP)
|
100% |
208
38.6 IPS |
|
|
Image Classification (Q)
|
100% |
604
112.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
258
4.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
257
4.17 IPS |
|
|
Image Segmentation (Q)
|
98% |
683
11.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
910
1.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
903
1.05 IPS |
|
|
Pose Estimation (Q)
|
84% |
1568
1.86 IPS |
|
|
Object Detection (SP)
|
100% |
159
12.6 IPS |
|
|
Object Detection (HP)
|
100% |
138
10.9 IPS |
|
|
Object Detection (Q)
|
83% |
568
45.9 IPS |
|
|
Face Detection (SP)
|
100% |
651
7.73 IPS |
|
|
Face Detection (HP)
|
100% |
647
7.69 IPS |
|
|
Face Detection (Q)
|
95% |
1416
16.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
838
6.46 IPS |
|
|
Depth Estimation (HP)
|
99% |
736
5.67 IPS |
|
|
Depth Estimation (Q)
|
64% |
1408
12.9 IPS |
|
|
Style Transfer (SP)
|
89% |
1648
2.14 IPS |
|
|
Style Transfer (HP)
|
89% |
1639
2.13 IPS |
|
|
Style Transfer (Q)
|
98% |
3439
4.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
431
15.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
424
15.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
812
30.1 IPS |
|
|
Text Classification (SP)
|
100% |
243
324.7 IPS |
|
|
Text Classification (HP)
|
100% |
248
331.1 IPS |
|
|
Text Classification (Q)
|
88% |
433
584.5 IPS |
|
|
Machine Translation (SP)
|
100% |
418
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
426
7.34 IPS |
|
|
Machine Translation (Q)
|
50% |
288
10.2 IPS |
