NbAiLab/borealis-open-12b

VISIONPricing:Input $0.2 / Output $0.6Concurrent Unit Cost:1Model Size:12BQuant:FP8Context Size:32kPublished:May 20, 2026License:gemmaArchitecture:Transformer Featherless Exclusive Cold

NbAiLab/borealis-open-12b is a 12-billion parameter instruction-tuned language model developed by the National Library of Norway, based on the Gemma 3 architecture. This open release model is fine-tuned for Norwegian-centric instruction following, excelling in tasks like drafting, summarization, and question answering in Norwegian. It is specifically designed for assistant-style tasks and assessing Norwegian writing, with a focus on Bokmål and Nynorsk.

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Borealis Open 12B: Norwegian-Centric Instruction Model

NbAiLab/borealis-open-12b is a 12-billion parameter instruction-tuned model from the National Library of Norway (NbAiLab), built upon the Gemma 3 family, specifically google/gemma-3-12b-it. This model is an "open release" variant, meaning it does not incorporate certain copyright-protected material used in the full Borealis models.

Key Capabilities & Features

  • Norwegian-Centric Instruction Following: Fine-tuned using a supervised fine-tuning (SFT) dataset, NbAiLab/aurora-sft-open, specifically prepared for Norwegian assistant behavior, writing, summarization, and Q&A.
  • Multilingual Focus: Optimized for Norwegian, Bokmål, and Nynorsk language tasks.
  • Safety Alignment: Utilizes "prompt baking" and weighted merging of SFT and aligned models to balance quality, usefulness, and safer behavior.
  • Gemma 3 Base: Leverages the robust architecture of Google's Gemma 3 models.

Intended Use Cases

  • Assistant-style tasks: Drafting, summarization, and question answering with a focus on Norwegian content.
  • Norwegian Writing Assessment: Useful for evaluating and improving Norwegian writing style and quality.
  • Language Coverage Evaluation: Ideal for assessing model behavior and language coverage for Norwegian dialects.

Limitations

As with all generative models, Borealis Open 12B may produce incorrect or biased outputs. Its performance outside Norwegian and English use cases has not been fully characterized, and it should not be used for safety-critical applications without additional safeguards.