samsung SM-F956W
Geekbench AI Score
350
Single Precision Score
21938
Half Precision Score
49790
Quantized Score
Geekbench AI 1.5.0-Beta1 Corporate for Android AArch64
Result Information
| Upload Date | September 02 2025 05:17 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-F956W |
| Model ID | samsung SM-F956W |
| 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 | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
225
41.8 IPS |
|
|
Image Classification (HP)
|
100% |
17014
3.16 KIPS |
|
|
Image Classification (Q)
|
97% |
41444
7.73 KIPS |
|
|
Image Segmentation (SP)
|
100% |
251
4.06 IPS |
|
|
Image Segmentation (HP)
|
100% |
10872
176.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
29344
477.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
376
0.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
100086
116.8 IPS |
|
|
Pose Estimation (Q)
|
98% |
397100
464.8 IPS |
|
|
Object Detection (SP)
|
100% |
190
15.0 IPS |
|
|
Object Detection (HP)
|
100% |
15633
1.24 KIPS |
|
|
Object Detection (Q)
|
86% |
19416
1.56 KIPS |
|
|
Face Detection (SP)
|
100% |
528
6.28 IPS |
|
|
Face Detection (HP)
|
100% |
32424
385.3 IPS |
|
|
Face Detection (Q)
|
97% |
109835
1.31 KIPS |
|
|
Depth Estimation (SP)
|
100% |
466
3.59 IPS |
|
|
Depth Estimation (HP)
|
99% |
63675
490.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
114965
1.08 KIPS |
|
|
Style Transfer (SP)
|
100% |
739
0.95 IPS |
|
|
Style Transfer (HP)
|
98% |
84984
109.6 IPS |
|
|
Style Transfer (Q)
|
98% |
422502
544.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
242
8.94 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
44202
1.63 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103627
3.84 KIPS |
|
|
Text Classification (SP)
|
100% |
286
382.0 IPS |
|
|
Text Classification (HP)
|
100% |
3083
4.12 KIPS |
|
|
Text Classification (Q)
|
93% |
6830
9.17 KIPS |
|
|
Machine Translation (SP)
|
100% |
557
9.60 IPS |
|
|
Machine Translation (HP)
|
100% |
3732
64.3 IPS |
|
|
Machine Translation (Q)
|
55% |
2645
69.3 IPS |
