alps k6878v1_64_ssdev
Geekbench ML Score
320
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 02:18 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
191
35.7 IPS |
|
|
Image Classification (F16)
|
100% |
252
47.1 IPS |
|
|
Image Classification (I8)
|
97% |
240
44.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
357
5.97 IPS |
|
|
Image Segmentation (F16)
|
100% |
413
6.89 IPS |
|
|
Image Segmentation (I8)
|
98% |
404
6.74 IPS |
|
|
Pose Estimation (F32)
|
100% |
183
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
245
0.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
244
0.30 IPS |
|
|
Object Detection (F32)
|
100% |
179
13.3 IPS |
|
|
Object Detection (F16)
|
100% |
226
16.9 IPS |
|
|
Object Detection (I8)
|
62% |
228
17.0 IPS |
|
|
Face Detection (F32)
|
100% |
709
8.42 IPS |
|
|
Face Detection (F16)
|
98% |
821
9.76 IPS |
|
|
Face Detection (I8)
|
86% |
759
9.02 IPS |
|
|
Depth Estimation (F32)
|
100% |
387
3.00 IPS |
|
|
Depth Estimation (F16)
|
100% |
487
3.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
485
3.76 IPS |
|
|
Style Transfer (F32)
|
100% |
977
1.29 IPS |
|
|
Style Transfer (F16)
|
100% |
1162
1.53 IPS |
|
|
Style Transfer (I8)
|
98% |
1161
1.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
228
8.15 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
251
8.97 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
250
8.93 IPS |
|
|
Text Classification (F32)
|
100% |
103
148.4 IPS |
|
|
Text Classification (F16)
|
100% |
106
152.8 IPS |
|
|
Text Classification (I8)
|
92% |
268
385.4 IPS |
|
|
Machine Translation (F32)
|
100% |
180
3.31 IPS |
|
|
Machine Translation (F16)
|
100% |
180
3.31 IPS |
|
|
Machine Translation (I8)
|
64% |
298
5.48 IPS |
