Samsone: A Family of Open Small Audio Language Models for On-Device Inference
The success of Large Audio Language Models has driven the development of massive multimodal networks exceeding billions of parameters. However, the demand for privacy-preserving, low-latency processing has shifted focus toward Small Audio Language Models (SALMs) capable of on-device execution. In this paper, we introduce Samsone, a family of SALMs designed for edge computing. Our core model, Samsone-134M, establishes a new state-of-the-art for its size class across multiple benchmarks. We further explore the scaling laws of SALMs by introducing Samsone-99M and Samsone-356M. Despite their compact footprint, the Samsone family delivers performance competitive with models orders of magnitude...
| Authors | Piotr Masztalski, Michał K. Grzeszczyk, Olaf Sikorski |
|---|---|
| Primary category | eess.AS |
| Published | 18 September 2026 |
| Last updated at source | 18 September 2026 |
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