samsung SM-X920
Geekbench ML Score
1480
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 05:01 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X920 |
| Model ID | samsung SM-X920 |
| Motherboard | gts10uwifi |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
830
155.4 IPS |
|
|
Image Classification (F16)
|
100% |
909
170.2 IPS |
|
|
Image Classification (I8)
|
97% |
1383
258.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1112
18.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1079
18.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1344
22.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1454
1.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
1398
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
6353
7.69 IPS |
|
|
Object Detection (F32)
|
100% |
744
55.5 IPS |
|
|
Object Detection (F16)
|
100% |
790
59.0 IPS |
|
|
Object Detection (I8)
|
61% |
1360
101.5 IPS |
|
|
Face Detection (F32)
|
100% |
1882
22.4 IPS |
|
|
Face Detection (F16)
|
100% |
1896
22.5 IPS |
|
|
Face Detection (I8)
|
86% |
2639
31.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1595
12.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
1600
12.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2641
20.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2363
3.11 IPS |
|
|
Style Transfer (F16)
|
100% |
2307
3.03 IPS |
|
|
Style Transfer (I8)
|
98% |
5199
6.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1065
38.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1038
37.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2749
98.2 IPS |
|
|
Text Classification (F32)
|
100% |
974
1.40 KIPS |
|
|
Text Classification (F16)
|
100% |
976
1.40 KIPS |
|
|
Text Classification (I8)
|
92% |
621
892.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1702
31.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1671
30.7 IPS |
|
|
Machine Translation (I8)
|
64% |
816
15.0 IPS |
