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 02:28 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% |
178
33.3 IPS |
|
|
Image Classification (F16)
|
100% |
237
44.3 IPS |
|
|
Image Classification (I8)
|
97% |
201
37.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
367
6.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
410
6.85 IPS |
|
|
Image Segmentation (I8)
|
98% |
421
7.04 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% |
163
12.2 IPS |
|
|
Object Detection (F16)
|
100% |
205
15.3 IPS |
|
|
Object Detection (I8)
|
62% |
209
15.6 IPS |
|
|
Face Detection (F32)
|
100% |
673
8.00 IPS |
|
|
Face Detection (F16)
|
98% |
765
9.10 IPS |
|
|
Face Detection (I8)
|
86% |
724
8.61 IPS |
|
|
Depth Estimation (F32)
|
100% |
383
2.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
480
3.72 IPS |
|
|
Depth Estimation (I8)
|
95% |
479
3.71 IPS |
|
|
Style Transfer (F32)
|
100% |
977
1.28 IPS |
|
|
Style Transfer (F16)
|
100% |
1154
1.52 IPS |
|
|
Style Transfer (I8)
|
98% |
1157
1.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
217
7.76 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
243
8.69 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
246
8.79 IPS |
|
|
Text Classification (F32)
|
100% |
104
149.7 IPS |
|
|
Text Classification (F16)
|
100% |
104
149.9 IPS |
|
|
Text Classification (I8)
|
92% |
269
386.7 IPS |
|
|
Machine Translation (F32)
|
100% |
185
3.40 IPS |
|
|
Machine Translation (F16)
|
100% |
186
3.42 IPS |
|
|
Machine Translation (I8)
|
64% |
292
5.37 IPS |
