Samsung Galaxy S24+
Geekbench AI Score
3529
Single Precision Score
25142
Half Precision Score
46903
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 13 2024 06:31 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926B |
| 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 | 6.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1594
296.4 IPS |
|
|
Image Classification (HP)
|
100% |
16971
3.16 KIPS |
|
|
Image Classification (Q)
|
100% |
32410
6.03 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3029
49.1 IPS |
|
|
Image Segmentation (HP)
|
97% |
12649
205.8 IPS |
|
|
Image Segmentation (Q)
|
96% |
28616
465.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
14642
17.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
88218
102.9 IPS |
|
|
Pose Estimation (Q)
|
97% |
302880
354.7 IPS |
|
|
Object Detection (SP)
|
100% |
1588
126.0 IPS |
|
|
Object Detection (HP)
|
100% |
14082
1.12 KIPS |
|
|
Object Detection (Q)
|
90% |
23402
1.87 KIPS |
|
|
Face Detection (SP)
|
100% |
5080
60.4 IPS |
|
|
Face Detection (HP)
|
100% |
40050
475.9 IPS |
|
|
Face Detection (Q)
|
97% |
101197
1.21 KIPS |
|
|
Depth Estimation (SP)
|
100% |
5595
43.1 IPS |
|
|
Depth Estimation (HP)
|
79% |
56842
451.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
106387
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
29078
37.4 IPS |
|
|
Style Transfer (HP)
|
99% |
171316
220.9 IPS |
|
|
Style Transfer (Q)
|
98% |
271336
349.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4147
153.1 IPS |
|
|
Image Super-Resolution (HP)
|
84% |
23019
865.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
58580
2.17 KIPS |
|
|
Text Classification (SP)
|
100% |
608
811.4 IPS |
|
|
Text Classification (HP)
|
100% |
6739
9.00 KIPS |
|
|
Text Classification (Q)
|
93% |
8078
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1284
22.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6256
107.8 IPS |
|
|
Machine Translation (Q)
|
56% |
5671
145.5 IPS |
