alps tb8775p1_64_titan_whitesnake_25b
Geekbench ML Score
311
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 02:48 AM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
179
33.6 IPS |
|
|
Image Classification (F16)
|
100% |
235
44.0 IPS |
|
|
Image Classification (I8)
|
97% |
190
35.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
353
5.90 IPS |
|
|
Image Segmentation (F16)
|
100% |
409
6.83 IPS |
|
|
Image Segmentation (I8)
|
98% |
417
6.96 IPS |
|
|
Pose Estimation (F32)
|
100% |
184
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
244
0.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
244
0.30 IPS |
|
|
Object Detection (F32)
|
100% |
158
11.8 IPS |
|
|
Object Detection (F16)
|
100% |
207
15.5 IPS |
|
|
Object Detection (I8)
|
62% |
207
15.5 IPS |
|
|
Face Detection (F32)
|
100% |
682
8.11 IPS |
|
|
Face Detection (F16)
|
98% |
784
9.32 IPS |
|
|
Face Detection (I8)
|
86% |
719
8.55 IPS |
|
|
Depth Estimation (F32)
|
100% |
383
2.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
481
3.73 IPS |
|
|
Depth Estimation (I8)
|
95% |
476
3.69 IPS |
|
|
Style Transfer (F32)
|
100% |
975
1.28 IPS |
|
|
Style Transfer (F16)
|
100% |
1156
1.52 IPS |
|
|
Style Transfer (I8)
|
98% |
1152
1.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
218
7.77 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
249
8.88 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
246
8.78 IPS |
|
|
Text Classification (F32)
|
100% |
105
150.3 IPS |
|
|
Text Classification (F16)
|
100% |
104
149.4 IPS |
|
|
Text Classification (I8)
|
92% |
269
386.1 IPS |
|
|
Machine Translation (F32)
|
100% |
185
3.41 IPS |
|
|
Machine Translation (F16)
|
100% |
185
3.41 IPS |
|
|
Machine Translation (I8)
|
64% |
293
5.39 IPS |
