Samsung Tab S6 Lite
Geekbench AI Score
123
Single Precision Score
166
Half Precision Score
157
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 16 2025 02:23 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 9611 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Tab S6 Lite |
| Model ID | samsung SM-P615 |
| Motherboard | exynos9611 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.74 GHz |
| Cluster 1 | 4 Cores @ 1.74 GHz |
| Cluster 2 | 4 Cores @ 2.31 GHz |
| Memory Information | |
|---|---|
| Size | 3.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
106
19.6 IPS |
|
|
Image Classification (HP)
|
100% |
170
31.5 IPS |
|
|
Image Classification (Q)
|
99% |
163
30.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
114
1.85 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.49 IPS |
|
|
Image Segmentation (Q)
|
98% |
151
2.45 IPS |
|
|
Pose Estimation (SP)
|
100% |
81
0.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
109
0.13 IPS |
|
|
Pose Estimation (Q)
|
96% |
109
0.13 IPS |
|
|
Object Detection (SP)
|
100% |
88
6.97 IPS |
|
|
Object Detection (HP)
|
100% |
151
12.0 IPS |
|
|
Object Detection (Q)
|
83% |
146
11.8 IPS |
|
|
Face Detection (SP)
|
100% |
345
4.10 IPS |
|
|
Face Detection (HP)
|
100% |
373
4.43 IPS |
|
|
Face Detection (Q)
|
97% |
351
4.19 IPS |
|
|
Depth Estimation (SP)
|
100% |
178
1.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
248
1.91 IPS |
|
|
Depth Estimation (Q)
|
62% |
201
1.90 IPS |
|
|
Style Transfer (SP)
|
100% |
333
0.43 IPS |
|
|
Style Transfer (HP)
|
100% |
549
0.71 IPS |
|
|
Style Transfer (Q)
|
98% |
545
0.70 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
117
4.32 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
176
6.50 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
153
5.68 IPS |
|
|
Text Classification (SP)
|
100% |
48
64.3 IPS |
|
|
Text Classification (HP)
|
100% |
49
64.9 IPS |
|
|
Text Classification (Q)
|
91% |
63
84.2 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (HP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (Q)
|
57% |
64
1.56 IPS |
