Indkal WB25SPMTA15P2
Geekbench AI Score
885
Single Precision Score
886
Half Precision Score
1949
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 13 2025 10:29 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Indkal WB25SPMTA15P2 |
| Model ID | Indkal WB25SPMTA15P2 |
| Motherboard | k6878v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 7.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
478
88.9 IPS |
|
|
Image Classification (HP)
|
100% |
480
89.2 IPS |
|
|
Image Classification (Q)
|
100% |
1521
282.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
543
8.81 IPS |
|
|
Image Segmentation (HP)
|
100% |
548
8.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
1760
28.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2058
2.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
2053
2.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
3553
4.21 IPS |
|
|
Object Detection (SP)
|
100% |
406
32.2 IPS |
|
|
Object Detection (HP)
|
100% |
430
34.1 IPS |
|
|
Object Detection (Q)
|
83% |
1310
105.8 IPS |
|
|
Face Detection (SP)
|
100% |
1018
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
1002
11.9 IPS |
|
|
Face Detection (Q)
|
95% |
3273
39.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1486
11.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
1475
11.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3140
28.8 IPS |
|
|
Style Transfer (SP)
|
89% |
3313
4.30 IPS |
|
|
Style Transfer (HP)
|
89% |
3308
4.29 IPS |
|
|
Style Transfer (Q)
|
98% |
8097
10.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
793
29.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
794
29.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1917
71.1 IPS |
|
|
Text Classification (SP)
|
100% |
492
656.9 IPS |
|
|
Text Classification (HP)
|
100% |
483
645.0 IPS |
|
|
Text Classification (Q)
|
88% |
887
1.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
698
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (Q)
|
50% |
449
15.9 IPS |
