alps k6878v1_64_ssdev
Geekbench ML Score
518
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 02:12 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
254
47.6 IPS |
|
|
Image Classification (F16)
|
100% |
253
47.4 IPS |
|
|
Image Classification (I8)
|
97% |
475
88.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
351
5.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
342
5.72 IPS |
|
|
Image Segmentation (I8)
|
98% |
547
9.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
536
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
533
0.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
2272
2.75 IPS |
|
|
Object Detection (F32)
|
100% |
264
19.7 IPS |
|
|
Object Detection (F16)
|
100% |
268
20.0 IPS |
|
|
Object Detection (I8)
|
61% |
497
37.1 IPS |
|
|
Face Detection (F32)
|
100% |
516
6.13 IPS |
|
|
Face Detection (F16)
|
100% |
523
6.21 IPS |
|
|
Face Detection (I8)
|
86% |
1139
13.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
540
4.19 IPS |
|
|
Depth Estimation (F16)
|
100% |
540
4.19 IPS |
|
|
Depth Estimation (I8)
|
95% |
1188
9.21 IPS |
|
|
Style Transfer (F32)
|
100% |
872
1.15 IPS |
|
|
Style Transfer (F16)
|
100% |
870
1.14 IPS |
|
|
Style Transfer (I8)
|
98% |
2597
3.42 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
313
11.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
311
11.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1036
37.0 IPS |
|
|
Text Classification (F32)
|
100% |
347
498.7 IPS |
|
|
Text Classification (F16)
|
100% |
348
500.1 IPS |
|
|
Text Classification (I8)
|
92% |
327
470.3 IPS |
|
|
Machine Translation (F32)
|
100% |
506
9.31 IPS |
|
|
Machine Translation (F16)
|
100% |
518
9.53 IPS |
|
|
Machine Translation (I8)
|
64% |
273
5.02 IPS |
