samsung SM-A366W
Geekbench AI Score
776
Single Precision Score
836
Half Precision Score
1477
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 04 2025 02:03 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A366W |
| Model ID | samsung SM-A366W |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
193
35.9 IPS |
|
|
Image Classification (HP)
|
100% |
448
83.3 IPS |
|
|
Image Classification (Q)
|
100% |
1434
266.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
522
8.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
517
8.39 IPS |
|
|
Image Segmentation (Q)
|
98% |
1459
23.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2007
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1946
2.27 IPS |
|
|
Pose Estimation (Q)
|
84% |
3752
4.45 IPS |
|
|
Object Detection (SP)
|
100% |
450
35.7 IPS |
|
|
Object Detection (HP)
|
100% |
436
34.6 IPS |
|
|
Object Detection (Q)
|
83% |
1367
110.5 IPS |
|
|
Face Detection (SP)
|
100% |
1100
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1100
13.1 IPS |
|
|
Face Detection (Q)
|
95% |
3360
40.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
788
6.07 IPS |
|
|
Depth Estimation (HP)
|
99% |
846
6.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
3402
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3648
4.74 IPS |
|
|
Style Transfer (HP)
|
89% |
3520
4.57 IPS |
|
|
Style Transfer (Q)
|
98% |
7542
9.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
846
31.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
849
31.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1861
68.9 IPS |
|
|
Text Classification (SP)
|
100% |
451
602.6 IPS |
|
|
Text Classification (HP)
|
100% |
450
601.0 IPS |
|
|
Text Classification (Q)
|
88% |
845
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
724
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (Q)
|
50% |
34
1.22 IPS |
