samsung SM-N975F
Geekbench AI Score
298
Single Precision Score
397
Half Precision Score
397
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | July 01 2025 06:29 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-N975F |
| Model ID | samsung SM-N975F |
| Motherboard | exynos9825 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 11.15 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
156
28.9 IPS |
|
|
Image Classification (HP)
|
100% |
159
29.6 IPS |
|
|
Image Classification (Q)
|
99% |
357
66.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
256
4.15 IPS |
|
|
Image Segmentation (HP)
|
100% |
316
5.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
406
6.60 IPS |
|
|
Pose Estimation (SP)
|
100% |
1151
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
4695
5.48 IPS |
|
|
Pose Estimation (Q)
|
98% |
997
1.17 IPS |
|
|
Object Detection (SP)
|
100% |
165
13.1 IPS |
|
|
Object Detection (HP)
|
100% |
164
13.0 IPS |
|
|
Object Detection (Q)
|
87% |
403
32.3 IPS |
|
|
Face Detection (SP)
|
100% |
419
4.97 IPS |
|
|
Face Detection (HP)
|
100% |
427
5.07 IPS |
|
|
Face Detection (Q)
|
97% |
793
9.46 IPS |
|
|
Depth Estimation (SP)
|
100% |
368
2.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
370
2.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
724
6.57 IPS |
|
|
Style Transfer (SP)
|
100% |
623
0.80 IPS |
|
|
Style Transfer (HP)
|
100% |
364
0.47 IPS |
|
|
Style Transfer (Q)
|
98% |
407
0.53 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
416
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
847
31.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
572
21.2 IPS |
|
|
Text Classification (SP)
|
100% |
47
62.8 IPS |
|
|
Text Classification (HP)
|
100% |
237
316.5 IPS |
|
|
Text Classification (Q)
|
91% |
47
63.6 IPS |
|
|
Machine Translation (SP)
|
100% |
400
6.89 IPS |
|
|
Machine Translation (HP)
|
100% |
219
3.78 IPS |
|
|
Machine Translation (Q)
|
57% |
271
6.62 IPS |
