Google corsola
Geekbench AI Score
458
Single Precision Score
458
Half Precision Score
856
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 27 2025 12:36 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google corsola |
| Model ID | Google corsola |
| Motherboard | kyogre |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.05 GHz |
| Memory Information | |
|---|---|
| Size | 3.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
198
36.8 IPS |
|
|
Image Classification (HP)
|
100% |
206
38.3 IPS |
|
|
Image Classification (Q)
|
100% |
585
108.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
256
4.14 IPS |
|
|
Image Segmentation (HP)
|
100% |
257
4.17 IPS |
|
|
Image Segmentation (Q)
|
98% |
649
10.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1002
1.17 IPS |
|
|
Pose Estimation (HP)
|
100% |
1025
1.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
1525
1.81 IPS |
|
|
Object Detection (SP)
|
100% |
209
16.5 IPS |
|
|
Object Detection (HP)
|
100% |
206
16.3 IPS |
|
|
Object Detection (Q)
|
83% |
587
47.4 IPS |
|
|
Face Detection (SP)
|
100% |
641
7.62 IPS |
|
|
Face Detection (HP)
|
100% |
633
7.52 IPS |
|
|
Face Detection (Q)
|
95% |
1330
15.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
786
6.06 IPS |
|
|
Depth Estimation (HP)
|
99% |
790
6.09 IPS |
|
|
Depth Estimation (Q)
|
64% |
1385
12.7 IPS |
|
|
Style Transfer (SP)
|
89% |
1736
2.25 IPS |
|
|
Style Transfer (HP)
|
89% |
1737
2.25 IPS |
|
|
Style Transfer (Q)
|
98% |
3510
4.53 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
436
16.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
431
15.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
831
30.8 IPS |
|
|
Text Classification (SP)
|
100% |
241
321.9 IPS |
|
|
Text Classification (HP)
|
100% |
238
318.1 IPS |
|
|
Text Classification (Q)
|
88% |
424
571.6 IPS |
|
|
Machine Translation (SP)
|
100% |
418
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
411
7.08 IPS |
|
|
Machine Translation (Q)
|
50% |
275
9.77 IPS |
