Samsung Galaxy S24+
Geekbench AI Score
3485
Single Precision Score
24783
Half Precision Score
46281
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 25 2025 03:45 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926N |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1609
299.3 IPS |
|
|
Image Classification (HP)
|
100% |
17152
3.19 KIPS |
|
|
Image Classification (Q)
|
100% |
32805
6.10 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2958
48.0 IPS |
|
|
Image Segmentation (HP)
|
97% |
12110
197.0 IPS |
|
|
Image Segmentation (Q)
|
96% |
27855
453.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
13584
15.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
86367
100.8 IPS |
|
|
Pose Estimation (Q)
|
97% |
302981
354.8 IPS |
|
|
Object Detection (SP)
|
100% |
1602
127.1 IPS |
|
|
Object Detection (HP)
|
100% |
13961
1.11 KIPS |
|
|
Object Detection (Q)
|
90% |
21254
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
5108
60.7 IPS |
|
|
Face Detection (HP)
|
100% |
39725
472.0 IPS |
|
|
Face Detection (Q)
|
97% |
98567
1.18 KIPS |
|
|
Depth Estimation (SP)
|
100% |
5433
41.9 IPS |
|
|
Depth Estimation (HP)
|
79% |
55740
442.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
106685
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
28481
36.6 IPS |
|
|
Style Transfer (HP)
|
99% |
171280
220.2 IPS |
|
|
Style Transfer (Q)
|
98% |
267851
345.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3988
147.3 IPS |
|
|
Image Super-Resolution (HP)
|
82% |
22390
844.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
59399
2.20 KIPS |
|
|
Text Classification (SP)
|
100% |
639
852.9 IPS |
|
|
Text Classification (HP)
|
100% |
6763
9.03 KIPS |
|
|
Text Classification (Q)
|
93% |
8366
11.2 KIPS |
|
|
Machine Translation (SP)
|
100% |
1269
21.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6078
104.7 IPS |
|
|
Machine Translation (Q)
|
56% |
5475
140.4 IPS |
