samsung SM-F966B
Geekbench AI Score
432
Single Precision Score
26680
Half Precision Score
58491
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | August 02 2025 01:02 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966B |
| Model ID | samsung SM-F966B |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
388
72.2 IPS |
|
|
Image Classification (HP)
|
100% |
21183
3.94 KIPS |
|
|
Image Classification (Q)
|
97% |
50081
9.35 KIPS |
|
|
Image Segmentation (SP)
|
100% |
351
5.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
13498
218.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
40227
654.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
443
0.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
122523
143.0 IPS |
|
|
Pose Estimation (Q)
|
98% |
473869
554.6 IPS |
|
|
Object Detection (SP)
|
100% |
248
19.7 IPS |
|
|
Object Detection (HP)
|
100% |
18522
1.47 KIPS |
|
|
Object Detection (Q)
|
85% |
21166
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
598
7.10 IPS |
|
|
Face Detection (HP)
|
100% |
39713
471.9 IPS |
|
|
Face Detection (Q)
|
97% |
120270
1.43 KIPS |
|
|
Depth Estimation (SP)
|
100% |
533
4.11 IPS |
|
|
Depth Estimation (HP)
|
99% |
81252
626.0 IPS |
|
|
Depth Estimation (Q)
|
63% |
135374
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
905
1.16 IPS |
|
|
Style Transfer (HP)
|
98% |
98257
126.7 IPS |
|
|
Style Transfer (Q)
|
98% |
487104
628.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
279
10.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52209
1.93 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
130621
4.84 KIPS |
|
|
Text Classification (SP)
|
100% |
317
423.1 IPS |
|
|
Text Classification (HP)
|
100% |
3883
5.18 KIPS |
|
|
Text Classification (Q)
|
93% |
7964
10.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
598
10.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4383
75.5 IPS |
|
|
Machine Translation (Q)
|
56% |
2812
72.4 IPS |
