alps k6991v1_64
Geekbench ML Score
511
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 22 2025 01:44 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | alps k6991v1_64 |
| Model ID | alps k6991v1_64 |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 0 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 4 Cores @ 2.10 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.10 GHz |
| Memory Information | |
|---|---|
| Size | 10.76 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
850
159.1 IPS |
|
|
Image Classification (F16)
|
100% |
890
166.5 IPS |
|
|
Image Classification (I8)
|
97% |
1027
192.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1097
18.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1223
20.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1419
23.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1209
1.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
1004
1.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
3776
4.57 IPS |
|
|
Object Detection (F32)
|
100% |
562
41.9 IPS |
|
|
Object Detection (F16)
|
100% |
443
33.0 IPS |
|
|
Object Detection (I8)
|
61% |
714
53.3 IPS |
|
|
Face Detection (F32)
|
100% |
422
5.01 IPS |
|
|
Face Detection (F16)
|
100% |
346
4.12 IPS |
|
|
Face Detection (I8)
|
86% |
806
9.59 IPS |
|
|
Depth Estimation (F32)
|
100% |
255
1.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
258
2.00 IPS |
|
|
Depth Estimation (I8)
|
95% |
607
4.71 IPS |
|
|
Style Transfer (F32)
|
100% |
458
0.60 IPS |
|
|
Style Transfer (F16)
|
100% |
470
0.62 IPS |
|
|
Style Transfer (I8)
|
98% |
1548
2.04 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
194
6.91 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
191
6.83 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
686
24.5 IPS |
|
|
Text Classification (F32)
|
100% |
169
242.6 IPS |
|
|
Text Classification (F16)
|
100% |
160
229.8 IPS |
|
|
Text Classification (I8)
|
92% |
231
331.6 IPS |
|
|
Machine Translation (F32)
|
100% |
224
4.12 IPS |
|
|
Machine Translation (F16)
|
100% |
210
3.86 IPS |
|
|
Machine Translation (I8)
|
64% |
134
2.47 IPS |
