alps k6878v1_64_ssdev
Geekbench ML Score
517
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 03:41 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% |
248
46.5 IPS |
|
|
Image Classification (F16)
|
100% |
248
46.4 IPS |
|
|
Image Classification (I8)
|
97% |
461
86.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
345
5.76 IPS |
|
|
Image Segmentation (F16)
|
100% |
345
5.76 IPS |
|
|
Image Segmentation (I8)
|
98% |
571
9.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
537
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
538
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
2311
2.80 IPS |
|
|
Object Detection (F32)
|
100% |
266
19.8 IPS |
|
|
Object Detection (F16)
|
100% |
267
19.9 IPS |
|
|
Object Detection (I8)
|
61% |
510
38.1 IPS |
|
|
Face Detection (F32)
|
100% |
526
6.25 IPS |
|
|
Face Detection (F16)
|
100% |
517
6.15 IPS |
|
|
Face Detection (I8)
|
86% |
1115
13.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
543
4.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
538
4.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
1156
8.96 IPS |
|
|
Style Transfer (F32)
|
100% |
875
1.15 IPS |
|
|
Style Transfer (F16)
|
100% |
878
1.16 IPS |
|
|
Style Transfer (I8)
|
98% |
2607
3.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
313
11.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
303
10.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1091
38.9 IPS |
|
|
Text Classification (F32)
|
100% |
350
503.0 IPS |
|
|
Text Classification (F16)
|
100% |
340
488.8 IPS |
|
|
Text Classification (I8)
|
92% |
326
469.1 IPS |
|
|
Machine Translation (F32)
|
100% |
496
9.13 IPS |
|
|
Machine Translation (F16)
|
100% |
511
9.40 IPS |
|
|
Machine Translation (I8)
|
64% |
275
5.06 IPS |
