alps k6878v1_64_ssdev
Geekbench ML Score
1508
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 04:39 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 | 7.20 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% |
1514
283.3 IPS |
|
|
Image Classification (I8)
|
97% |
4574
855.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
546
9.12 IPS |
|
|
Image Segmentation (F16)
|
100% |
1559
26.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1975
33.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
2640
3.20 IPS |
|
|
Pose Estimation (F16)
|
100% |
5301
6.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
26073
31.6 IPS |
|
|
Object Detection (F32)
|
100% |
313
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
902
67.4 IPS |
|
|
Object Detection (I8)
|
64% |
1764
131.7 IPS |
|
|
Face Detection (F32)
|
100% |
1309
15.6 IPS |
|
|
Face Detection (F16)
|
97% |
3738
44.5 IPS |
|
|
Face Detection (I8)
|
86% |
8704
103.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
401
3.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
6938
53.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
13647
105.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1641
2.16 IPS |
|
|
Style Transfer (F16)
|
100% |
1460
1.92 IPS |
|
|
Style Transfer (I8)
|
31% |
4394
5.78 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
970
34.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4259
152.1 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
10495
374.8 IPS |
|
|
Text Classification (F32)
|
100% |
68
97.7 IPS |
|
|
Text Classification (F16)
|
100% |
568
816.5 IPS |
|
|
Text Classification (I8)
|
92% |
856
1.23 KIPS |
|
|
Machine Translation (F32)
|
100% |
184
3.38 IPS |
|
|
Machine Translation (F16)
|
100% |
179
3.30 IPS |
|
|
Machine Translation (I8)
|
66% |
312
5.75 IPS |
