From Data to Device: ELMOD An Efficient German-First 2.7B Language Model for Mobile Inference
We present ELMOD - Efficient Language Model for On-Device Deployment - a compact (2.7B) German language model designed for efficient inference on resource-constrained hardware. ELMOD was trained on a limited computational budget (55k H100 GPU hours) using exclusively publicly available data. We developed a suite of German-specific data pre-processing, which differ from English-oriented counterparts in their handling of morphological variation, compounding, and orthographic conventions. Furthermore, we introduced a quality filtering and rephrasing step, which increased the instructional quality of the data, improved performance during the annealing phase, and reduced overall compute requir...
| Authors | Darina Gold, Alexander Schwirjow, Viktor Haag et al. |
|---|---|
| Primary category | cs.CL |
| Published | 27 July 2026 |
| Last updated at source | 27 July 2026 |
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