Samsung Galaxy Tab S8 Ultra
Geekbench ML Score
579
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 28 2025 02:54 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy Tab S8 Ultra |
| Model ID | samsung SM-X900 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 11.01 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
331
61.9 IPS |
|
|
Image Classification (F16)
|
100% |
297
55.6 IPS |
|
|
Image Classification (I8)
|
97% |
447
83.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
397
6.64 IPS |
|
|
Image Segmentation (F16)
|
100% |
380
6.35 IPS |
|
|
Image Segmentation (I8)
|
98% |
428
7.15 IPS |
|
|
Pose Estimation (F32)
|
100% |
693
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
688
0.83 IPS |
|
|
Pose Estimation (I8)
|
100% |
2536
3.07 IPS |
|
|
Object Detection (F32)
|
100% |
296
22.1 IPS |
|
|
Object Detection (F16)
|
100% |
291
21.7 IPS |
|
|
Object Detection (I8)
|
61% |
536
40.0 IPS |
|
|
Face Detection (F32)
|
100% |
658
7.83 IPS |
|
|
Face Detection (F16)
|
100% |
663
7.88 IPS |
|
|
Face Detection (I8)
|
86% |
1000
11.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
651
5.05 IPS |
|
|
Depth Estimation (F16)
|
100% |
659
5.11 IPS |
|
|
Depth Estimation (I8)
|
95% |
742
5.76 IPS |
|
|
Style Transfer (F32)
|
100% |
1277
1.68 IPS |
|
|
Style Transfer (F16)
|
100% |
1350
1.78 IPS |
|
|
Style Transfer (I8)
|
98% |
2858
3.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
413
14.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
419
15.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1346
48.1 IPS |
|
|
Text Classification (F32)
|
100% |
420
603.2 IPS |
|
|
Text Classification (F16)
|
100% |
398
572.0 IPS |
|
|
Text Classification (I8)
|
92% |
185
265.2 IPS |
|
|
Machine Translation (F32)
|
100% |
620
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
582
10.7 IPS |
|
|
Machine Translation (I8)
|
64% |
270
4.97 IPS |
