samsung SM-A366W
Geekbench AI Score
928
Single Precision Score
1642
Half Precision Score
2063
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 01 2026 07:46 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 5.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
454
84.5 IPS |
|
|
Image Classification (HP)
|
100% |
938
174.4 IPS |
|
|
Image Classification (Q)
|
99% |
1436
267.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
539
8.74 IPS |
|
|
Image Segmentation (HP)
|
100% |
1048
17.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1675
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2033
2.37 IPS |
|
|
Pose Estimation (HP)
|
92% |
4157
4.88 IPS |
|
|
Pose Estimation (Q)
|
96% |
3696
4.33 IPS |
|
|
Object Detection (SP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (HP)
|
97% |
891
70.9 IPS |
|
|
Object Detection (Q)
|
85% |
1351
108.8 IPS |
|
|
Face Detection (SP)
|
100% |
1143
13.6 IPS |
|
|
Face Detection (HP)
|
100% |
2165
25.7 IPS |
|
|
Face Detection (Q)
|
97% |
3416
40.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1583
12.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
3189
24.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
3292
30.4 IPS |
|
|
Style Transfer (SP)
|
89% |
3721
4.83 IPS |
|
|
Style Transfer (HP)
|
88% |
4853
6.30 IPS |
|
|
Style Transfer (Q)
|
98% |
8266
10.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
865
32.0 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1719
63.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2075
76.9 IPS |
|
|
Text Classification (SP)
|
100% |
490
653.8 IPS |
|
|
Text Classification (HP)
|
100% |
799
1.07 KIPS |
|
|
Text Classification (Q)
|
93% |
944
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
741
12.8 IPS |
|
|
Machine Translation (HP)
|
96% |
851
14.7 IPS |
|
|
Machine Translation (Q)
|
55% |
639
17.2 IPS |
