Samtool Supported Models !!exclusive!! Jun 2026

(e.g., SM-G9980 BIT D, SM-N981U BIT D, SM-N986U BIT D)

The name has been used for other projects, such as a semantic segmentation dataset creation tool powered by the SAM model, which provides a web interface for manual labeling.

Once installed, you can begin integrating it into your Python scripts.

Standard SAM models are trained on everyday photography. To segment specialized imagery, developers have fine-tuned SAM for niche industries. Medical Imaging: MedSAM : CT scans, MRIs, X-rays, and ultrasound images. samtool supported models

For applications requiring real-time performance on resource-constrained devices (like mobile phones or edge computing devices), lightweight variants have been developed. , for example, is a model that drastically reduces the computational burden by re-architecting the original SAM's heavy transformer-based decoder into a more efficient convolutional neural network (CNN) design. These lightweight models aim to provide a significant speedup (e.g., 50x faster inference) while maintaining a reasonable level of segmentation quality, making them suitable for real-world, interactive systems.

: Highest segmentation quality and zero-shot performance, but requires significant VRAM and compute time. 2. Next-Generation Official Evolution: SAM 2

Before diving into the list, it is crucial to understand that SAMTool’s compatibility is largely dictated by rather than just the model number. SAMTool generally splits support into two major categories: , for example, is a model that drastically

If a device listed under the official documentation fails to respond to SamsTool, check the following hardware and software parameters:

| Model/Command | Time (real) | Peak RAM | Output size (VCF) | | :--- | :--- | :--- | :--- | | samtools view -h in.bam chr1 (extract) | 12s | 1.2GB | 4.5GB (SAM) | | Model B: samtools sort -@8 (8 threads) | 14m 22s | 6.8GB | 95GB (BAM) | | Model C: samtools mpileup -uf ref.fa in.bam | bcftools call -mv | 48m 31s | 2.1GB | 2.3MB (VCF) | | Model D: GATK HaplotypeCaller (for comparison) | 3h 12m | 8.7GB | 3.1MB (VCF) |

: Found in widespread mid-rangers like the Galaxy A54 5G (Exynos 8835). Exynos 1280 : Powers volume-sellers such as the Galaxy A33 5G Go to product viewer dialog for this item. and A53 5G (Exynos 881). making them suitable for real-world

For somatic mutation calling, SAMtools provides samtools mpileup with the -B (disable BAQ) flag for tumor samples to avoid over-filtering, followed by with the -c (consensus caller) or somatic-specific priors.

Used for factory resets and changing CSC codes on models newer than the Galaxy S7. According to SamFW tutorials, this works reliably on almost all devices up to the latest Android versions.