alps k6991v1_64
Geekbench ML Score
621
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 21 2025 08:27 AM |
| Views | 6 |
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% |
817
152.9 IPS |
|
|
Image Classification (F16)
|
100% |
901
168.6 IPS |
|
|
Image Classification (I8)
|
97% |
1093
204.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1244
20.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1228
20.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1357
22.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1329
1.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
1214
1.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
5468
6.62 IPS |
|
|
Object Detection (F32)
|
100% |
772
57.7 IPS |
|
|
Object Detection (F16)
|
100% |
811
60.5 IPS |
|
|
Object Detection (I8)
|
61% |
958
71.6 IPS |
|
|
Face Detection (F32)
|
100% |
1590
18.9 IPS |
|
|
Face Detection (F16)
|
100% |
942
11.2 IPS |
|
|
Face Detection (I8)
|
86% |
1138
13.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
260
2.02 IPS |
|
|
Depth Estimation (F16)
|
100% |
261
2.02 IPS |
|
|
Depth Estimation (I8)
|
95% |
653
5.06 IPS |
|
|
Style Transfer (F32)
|
100% |
476
0.63 IPS |
|
|
Style Transfer (F16)
|
100% |
479
0.63 IPS |
|
|
Style Transfer (I8)
|
98% |
1560
2.05 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
205
7.31 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
199
7.11 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
644
23.0 IPS |
|
|
Text Classification (F32)
|
100% |
164
235.6 IPS |
|
|
Text Classification (F16)
|
100% |
159
228.1 IPS |
|
|
Text Classification (I8)
|
92% |
257
368.9 IPS |
|
|
Machine Translation (F32)
|
100% |
294
5.42 IPS |
|
|
Machine Translation (F16)
|
100% |
277
5.10 IPS |
|
|
Machine Translation (I8)
|
64% |
185
3.40 IPS |
