alps k6878v1_64_ssdev
Geekbench ML Score
1546
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2025 08:12 AM |
| Views | 2 |
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 | 7.13 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
424
79.4 IPS |
|
|
Image Classification (F16)
|
100% |
1504
281.4 IPS |
|
|
Image Classification (I8)
|
97% |
4433
829.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
544
9.09 IPS |
|
|
Image Segmentation (F16)
|
100% |
1593
26.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1996
33.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
2576
3.12 IPS |
|
|
Pose Estimation (F16)
|
100% |
5462
6.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
26032
31.5 IPS |
|
|
Object Detection (F32)
|
100% |
313
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
1172
87.5 IPS |
|
|
Object Detection (I8)
|
64% |
1794
133.9 IPS |
|
|
Face Detection (F32)
|
100% |
1310
15.6 IPS |
|
|
Face Detection (F16)
|
97% |
3788
45.0 IPS |
|
|
Face Detection (I8)
|
86% |
8708
103.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
399
3.10 IPS |
|
|
Depth Estimation (F16)
|
100% |
6929
53.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
16386
127.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1642
2.16 IPS |
|
|
Style Transfer (F16)
|
100% |
1468
1.93 IPS |
|
|
Style Transfer (I8)
|
31% |
4378
5.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
963
34.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4003
143.0 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
10536
376.3 IPS |
|
|
Text Classification (F32)
|
100% |
66
94.9 IPS |
|
|
Text Classification (F16)
|
100% |
747
1.07 KIPS |
|
|
Text Classification (I8)
|
92% |
944
1.36 KIPS |
|
|
Machine Translation (F32)
|
100% |
183
3.37 IPS |
|
|
Machine Translation (F16)
|
100% |
185
3.40 IPS |
|
|
Machine Translation (I8)
|
66% |
310
5.70 IPS |
