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 03:56 AM |
| Views | 1 |
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% |
419
78.5 IPS |
|
|
Image Classification (F16)
|
100% |
1518
284.1 IPS |
|
|
Image Classification (I8)
|
97% |
4526
847.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
544
9.08 IPS |
|
|
Image Segmentation (F16)
|
100% |
1574
26.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1988
33.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
2652
3.21 IPS |
|
|
Pose Estimation (F16)
|
100% |
5905
7.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
26117
31.6 IPS |
|
|
Object Detection (F32)
|
100% |
315
23.6 IPS |
|
|
Object Detection (F16)
|
100% |
932
69.6 IPS |
|
|
Object Detection (I8)
|
64% |
1786
133.3 IPS |
|
|
Face Detection (F32)
|
100% |
1309
15.6 IPS |
|
|
Face Detection (F16)
|
97% |
3747
44.6 IPS |
|
|
Face Detection (I8)
|
86% |
8708
103.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
401
3.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
6932
53.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
14197
110.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1644
2.16 IPS |
|
|
Style Transfer (F16)
|
100% |
1473
1.94 IPS |
|
|
Style Transfer (I8)
|
31% |
4380
5.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
969
34.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4257
152.0 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
10467
373.8 IPS |
|
|
Text Classification (F32)
|
100% |
68
98.3 IPS |
|
|
Text Classification (F16)
|
100% |
634
910.7 IPS |
|
|
Text Classification (I8)
|
92% |
829
1.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
184
3.39 IPS |
|
|
Machine Translation (F16)
|
100% |
179
3.29 IPS |
|
|
Machine Translation (I8)
|
66% |
313
5.75 IPS |
