Samsung Galaxy S24
Geekbench AI Score
2142
Single Precision Score
2060
Half Precision Score
2970
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Technologov |
| Upload Date | May 04 2025 01:53 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 |
| Model ID | samsung SM-S921B |
| 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 | 7.06 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1863
346.4 IPS |
|
|
Image Classification (HP)
|
100% |
1767
328.6 IPS |
|
|
Image Classification (Q)
|
100% |
3192
593.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2457
39.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2342
38.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
3557
57.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
3951
4.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
3770
4.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
6383
7.57 IPS |
|
|
Object Detection (SP)
|
98% |
1364
108.5 IPS |
|
|
Object Detection (HP)
|
98% |
1332
106.0 IPS |
|
|
Object Detection (Q)
|
83% |
1804
145.7 IPS |
|
|
Face Detection (SP)
|
100% |
3200
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
2608
31.0 IPS |
|
|
Face Detection (Q)
|
95% |
4302
51.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
2970
22.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2946
22.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
4517
41.4 IPS |
|
|
Style Transfer (SP)
|
89% |
7371
9.57 IPS |
|
|
Style Transfer (HP)
|
89% |
7201
9.35 IPS |
|
|
Style Transfer (Q)
|
98% |
13578
17.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1508
55.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1569
57.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3256
120.6 IPS |
|
|
Text Classification (SP)
|
100% |
530
707.7 IPS |
|
|
Text Classification (HP)
|
99% |
567
756.7 IPS |
|
|
Text Classification (Q)
|
88% |
836
1.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
1477
25.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1346
23.2 IPS |
|
|
Machine Translation (Q)
|
50% |
570
20.2 IPS |
