alps tb8775p1_64_titan_whitesnake_25b
Geekbench ML Score
1660
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2025 05:41 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps tb8775p1_64_titan_whitesnake_25b |
| Model ID | alps tb8775p1_64_titan_whitesnake_25b |
| Motherboard | tb8775p1_64_titan_whitesnake_25b |
| 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 | 5.16 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
464
86.8 IPS |
|
|
Image Classification (F16)
|
100% |
1698
317.8 IPS |
|
|
Image Classification (I8)
|
97% |
4740
886.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
588
9.82 IPS |
|
|
Image Segmentation (F16)
|
100% |
1796
30.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
2139
35.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
2898
3.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
5062
6.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
26870
32.5 IPS |
|
|
Object Detection (F32)
|
100% |
335
25.0 IPS |
|
|
Object Detection (F16)
|
100% |
1255
93.7 IPS |
|
|
Object Detection (I8)
|
64% |
1949
145.5 IPS |
|
|
Face Detection (F32)
|
100% |
1465
17.4 IPS |
|
|
Face Detection (F16)
|
97% |
4508
53.6 IPS |
|
|
Face Detection (I8)
|
86% |
9875
117.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
420
3.26 IPS |
|
|
Depth Estimation (F16)
|
100% |
7595
58.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
12944
100.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1695
2.23 IPS |
|
|
Style Transfer (F16)
|
100% |
1587
2.09 IPS |
|
|
Style Transfer (I8)
|
31% |
4472
5.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1117
39.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4431
158.3 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
10394
371.2 IPS |
|
|
Text Classification (F32)
|
100% |
67
96.4 IPS |
|
|
Text Classification (F16)
|
100% |
979
1.41 KIPS |
|
|
Text Classification (I8)
|
92% |
1196
1.72 KIPS |
|
|
Machine Translation (F32)
|
100% |
190
3.49 IPS |
|
|
Machine Translation (F16)
|
100% |
188
3.46 IPS |
|
|
Machine Translation (I8)
|
66% |
316
5.82 IPS |
