alps k6878v1_64_ssdev
Geekbench ML Score
1516
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2025 04:51 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps k6878v1_64_ssdev |
| Model ID | alps k6878v1_64_ssdev |
| 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 @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 7.20 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
427
79.9 IPS |
|
|
Image Classification (F16)
|
100% |
1523
284.9 IPS |
|
|
Image Classification (I8)
|
97% |
4583
857.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
546
9.12 IPS |
|
|
Image Segmentation (F16)
|
100% |
1579
26.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1999
33.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
2586
3.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
5135
6.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
26144
31.7 IPS |
|
|
Object Detection (F32)
|
100% |
314
23.4 IPS |
|
|
Object Detection (F16)
|
100% |
961
71.8 IPS |
|
|
Object Detection (I8)
|
64% |
1794
134.0 IPS |
|
|
Face Detection (F32)
|
100% |
1311
15.6 IPS |
|
|
Face Detection (F16)
|
97% |
3779
44.9 IPS |
|
|
Face Detection (I8)
|
86% |
8818
104.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
400
3.10 IPS |
|
|
Depth Estimation (F16)
|
100% |
6936
53.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
13491
104.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1644
2.16 IPS |
|
|
Style Transfer (F16)
|
100% |
1449
1.91 IPS |
|
|
Style Transfer (I8)
|
31% |
4387
5.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
970
34.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4261
152.2 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
10680
381.4 IPS |
|
|
Text Classification (F32)
|
100% |
68
97.7 IPS |
|
|
Text Classification (F16)
|
100% |
575
826.8 IPS |
|
|
Text Classification (I8)
|
92% |
882
1.27 KIPS |
|
|
Machine Translation (F32)
|
100% |
185
3.40 IPS |
|
|
Machine Translation (F16)
|
100% |
182
3.34 IPS |
|
|
Machine Translation (I8)
|
66% |
317
5.84 IPS |
