samsung SM-S921Q
Geekbench ML Score
1667
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 09 2024 11:19 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S921Q |
| Model ID | samsung SM-S921Q |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 6.93 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
783
146.6 IPS |
|
|
Image Classification (F16)
|
100% |
1438
269.0 IPS |
|
|
Image Classification (I8)
|
99% |
1059
198.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1368
22.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
2682
44.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
2281
38.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1083
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
2662
3.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
2664
3.23 IPS |
|
|
Object Detection (F32)
|
100% |
714
53.3 IPS |
|
|
Object Detection (F16)
|
100% |
713
53.2 IPS |
|
|
Object Detection (I8)
|
62% |
441
32.9 IPS |
|
|
Face Detection (F32)
|
100% |
2845
33.8 IPS |
|
|
Face Detection (F16)
|
97% |
5259
62.5 IPS |
|
|
Face Detection (I8)
|
86% |
4586
54.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1898
14.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
4094
31.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
4027
31.2 IPS |
|
|
Style Transfer (F32)
|
100% |
7231
9.51 IPS |
|
|
Style Transfer (F16)
|
100% |
11692
15.4 IPS |
|
|
Style Transfer (I8)
|
98% |
11704
15.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
576
20.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1844
65.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1823
65.1 IPS |
|
|
Text Classification (F32)
|
100% |
450
646.8 IPS |
|
|
Text Classification (F16)
|
100% |
453
650.8 IPS |
|
|
Text Classification (I8)
|
92% |
733
1.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
724
13.3 IPS |
|
|
Machine Translation (F16)
|
100% |
717
13.2 IPS |
|
|
Machine Translation (I8)
|
64% |
839
15.4 IPS |
