alps aiv8195p1_64_bsp
Geekbench ML Score
297
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 02:37 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | alps aiv8195p1_64_bsp |
| Model ID | alps aiv8195p1_64_bsp |
| Motherboard | aiv8195p1_64_bsp |
| 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 @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 6.98 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
186
34.8 IPS |
|
|
Image Classification (F16)
|
100% |
280
52.4 IPS |
|
|
Image Classification (I8)
|
97% |
256
47.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
232
3.87 IPS |
|
|
Image Segmentation (F16)
|
100% |
316
5.27 IPS |
|
|
Image Segmentation (I8)
|
98% |
307
5.13 IPS |
|
|
Pose Estimation (F32)
|
100% |
182
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
216
0.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
216
0.26 IPS |
|
|
Object Detection (F32)
|
100% |
98
7.29 IPS |
|
|
Object Detection (F16)
|
100% |
136
10.2 IPS |
|
|
Object Detection (I8)
|
62% |
120
8.95 IPS |
|
|
Face Detection (F32)
|
100% |
493
5.87 IPS |
|
|
Face Detection (F16)
|
98% |
565
6.72 IPS |
|
|
Face Detection (I8)
|
86% |
531
6.31 IPS |
|
|
Depth Estimation (F32)
|
100% |
336
2.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
435
3.37 IPS |
|
|
Depth Estimation (I8)
|
95% |
438
3.40 IPS |
|
|
Style Transfer (F32)
|
100% |
707
0.93 IPS |
|
|
Style Transfer (F16)
|
100% |
1003
1.32 IPS |
|
|
Style Transfer (I8)
|
98% |
986
1.30 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
177
6.33 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
258
9.22 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
253
9.03 IPS |
|
|
Text Classification (F32)
|
100% |
185
265.6 IPS |
|
|
Text Classification (F16)
|
100% |
185
266.1 IPS |
|
|
Text Classification (I8)
|
92% |
350
502.9 IPS |
|
|
Machine Translation (F32)
|
100% |
351
6.46 IPS |
|
|
Machine Translation (F16)
|
100% |
332
6.11 IPS |
|
|
Machine Translation (I8)
|
64% |
351
6.45 IPS |
