alps k6878v1_64_ssdev
Geekbench ML Score
1522
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 05:20 AM |
| Views | 7 |
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% |
423
79.1 IPS |
|
|
Image Classification (F16)
|
100% |
1521
284.6 IPS |
|
|
Image Classification (I8)
|
97% |
4546
850.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
543
9.07 IPS |
|
|
Image Segmentation (F16)
|
100% |
1557
26.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1983
33.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
2576
3.12 IPS |
|
|
Pose Estimation (F16)
|
100% |
5460
6.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
26105
31.6 IPS |
|
|
Object Detection (F32)
|
100% |
312
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
986
73.6 IPS |
|
|
Object Detection (I8)
|
64% |
1768
132.0 IPS |
|
|
Face Detection (F32)
|
100% |
1308
15.6 IPS |
|
|
Face Detection (F16)
|
97% |
3758
44.7 IPS |
|
|
Face Detection (I8)
|
86% |
8826
104.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
400
3.10 IPS |
|
|
Depth Estimation (F16)
|
100% |
6929
53.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
14307
110.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1641
2.16 IPS |
|
|
Style Transfer (F16)
|
100% |
1461
1.92 IPS |
|
|
Style Transfer (I8)
|
31% |
4378
5.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
968
34.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4261
152.2 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
10364
370.1 IPS |
|
|
Text Classification (F32)
|
100% |
68
97.1 IPS |
|
|
Text Classification (F16)
|
100% |
657
944.0 IPS |
|
|
Text Classification (I8)
|
92% |
868
1.25 KIPS |
|
|
Machine Translation (F32)
|
100% |
184
3.38 IPS |
|
|
Machine Translation (F16)
|
100% |
179
3.29 IPS |
|
|
Machine Translation (I8)
|
66% |
312
5.75 IPS |
