Samsung Galaxy S24 Ultra
Geekbench AI Score
466
Single Precision Score
466
Half Precision Score
1066
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 05 2026 06:33 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928N |
| 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 | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
296
55.0 IPS |
|
|
Image Classification (HP)
|
100% |
299
55.6 IPS |
|
|
Image Classification (Q)
|
99% |
771
143.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
372
6.03 IPS |
|
|
Image Segmentation (HP)
|
100% |
375
6.08 IPS |
|
|
Image Segmentation (Q)
|
98% |
761
12.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
501
0.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
483
0.56 IPS |
|
|
Pose Estimation (Q)
|
98% |
1892
2.21 IPS |
|
|
Object Detection (SP)
|
100% |
274
21.7 IPS |
|
|
Object Detection (HP)
|
100% |
275
21.8 IPS |
|
|
Object Detection (Q)
|
87% |
791
63.4 IPS |
|
|
Face Detection (SP)
|
100% |
673
7.99 IPS |
|
|
Face Detection (HP)
|
100% |
678
8.05 IPS |
|
|
Face Detection (Q)
|
97% |
1624
19.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
585
4.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
585
4.50 IPS |
|
|
Depth Estimation (Q)
|
64% |
1402
12.7 IPS |
|
|
Style Transfer (SP)
|
100% |
963
1.24 IPS |
|
|
Style Transfer (HP)
|
100% |
963
1.24 IPS |
|
|
Style Transfer (Q)
|
98% |
2375
3.06 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
315
11.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
318
11.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1058
39.2 IPS |
|
|
Text Classification (SP)
|
100% |
416
554.7 IPS |
|
|
Text Classification (HP)
|
100% |
420
560.5 IPS |
|
|
Text Classification (Q)
|
91% |
692
929.7 IPS |
|
|
Machine Translation (SP)
|
100% |
649
11.2 IPS |
|
|
Machine Translation (HP)
|
100% |
645
11.1 IPS |
|
|
Machine Translation (Q)
|
57% |
546
13.3 IPS |
