NbAiLab/borealis-27b

VISIONPricing:Input $0.4 / Cached $0.08 / Output $1.2Concurrent Unit Cost:2Model Size:27BQuant:FP8Context Size:32kPublished:May 20, 2026License:otherArchitecture:Transformer0.0K Featherless Exclusive Cold

NbAiLab/borealis-27b is a 27 billion parameter instruction-tuned model from the National Library of Norway, based on the Gemma 3 family. This full release model is fine-tuned for Norwegian-centric instruction following, leveraging a unique dataset including copyrighted Norwegian press material. It is designed for assistant-style tasks, writing, summarization, and question answering in Norwegian, Bokmål, and Nynorsk.

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Borealis 27B: Norwegian-Centric Instruction Model

NbAiLab/borealis-27b is a 27 billion parameter instruction-tuned model developed by the National Library of Norway (Nasjonalbiblioteket, NB). It is built upon the Gemma 3 architecture, specifically fine-tuned from google/gemma-3-27b-it.

Key Differentiators & Capabilities

  • Norwegian Language Focus: This model is specifically instruction-tuned for Norwegian-centric tasks, including assistant behavior, writing, summarization, and question answering.
  • Unique Training Data: It incorporates a limited subset of data from an agreement with Norwegian rights-holder organizations, including copyrighted press material, to enhance its understanding and generation of Norwegian news article titles and ingress texts. The SFT dataset, NbAiLab/aurora-sft, includes 10k tasks derived from this material.
  • Safety Alignment: Utilizes "prompt baking" and weighted merging of SFT and aligned models to balance quality, usefulness, and safer behavior.

Intended Use Cases

  • Norwegian-centric assistant-style tasks, such as drafting, summarization, and Q&A.
  • Assessment and improvement of Norwegian writing style and quality.
  • Evaluation of behavior and language coverage for Norwegian, Bokmål, and Nynorsk.

Limitations

  • May produce incorrect or biased outputs.
  • Not recommended for safety-critical applications without additional safeguards.
  • Performance outside Norwegian and English use cases is not fully characterized.