State-of-the-art Danish Models
These models constitute state-of-the-art models for Danish within their respective domain (highlighted below the model).
24B • Updated • 242k • 1.37kNote Among the best performing open-weight ~10-100b generative models which has been instruction-tuned. Determined by EuroEval Danish NLG (2025/11/04).
google/gemma-3-27b-it
Image-Text-to-Text • 27B • Updated • 1.07M • • 1.99kNote Among the best performing open-weight ~10-100b generative models which has been instruction-tuned. Determined by EuroEval Danish NLG (2025/11/04).
google/gemma-3n-E4B-it
Image-Text-to-Text • 8B • Updated • 21.7k • • 919Note Among the best performing open-weight ~7-9b generative models which has been instruction-tuned. Determined by EuroEval Danish NLG (2025/11/04).
google/gemma-2-9b-it
Text Generation • 9B • Updated • 344k • • 832Note Among the best performing open-weight ~7-9b generative models which has been instruction-tuned. Determined by EuroEval Danish NLG (2025/11/04).
google/gemma-2-9b
Text Generation • 9B • Updated • 73.5k • • 713Note Among the best performing open-weight ~7-9b generative models which hasn't been instruction-tuned. Determined by EuroEval Danish NLG (2025/11/04).
KennethEnevoldsen/dfm-sentence-encoder-large
Feature Extraction • 0.4B • Updated • 386 • 3Note Among the best large-sized encoder for Danish determined by EuroEval Danish NLU (2025/11/04)
AI-Sweden-Models/roberta-large-1160k
Fill-Mask • 0.4B • Updated • 158 • 11Note Among the best large-sized encoder for Danish determined by EuroEval Danish NLU (2025/11/04)
KennethEnevoldsen/dfm-sentence-encoder-medium
Sentence Similarity • Updated • 62Note Among the best medium-sized encoder for Danish determined by EuroEval Danish NLU (2025/11/04)
ltg/norbert3-small
Fill-Mask • Updated • 243 • 2Note Among the best small sized encoder for Danish as determined by EuroEval Danish NLU (2025/11/04)
syvai/hviske-v3-conversation
Automatic Speech Recognition • 2B • Updated • 405 • 11Note Automatic speech recognition based on Whisper 3 and fine-tuned on CoRal Obtains the lowest word error rate on CoRal conversations (2025/11/04), might be slightly overfit
openai/whisper-large-v3
Automatic Speech Recognition • 2B • Updated • 5.75M • • 5.88kNote Automatic speech recognition (ASR) Best multilingual ASR model for Danish (2025/11/04)
CoRal-project/roest-v2-wav2vec2-315m
Automatic Speech Recognition • 0.3B • Updated • 1.51k • 6Note Speech Encoder (Wav2Vec2.0) The encoder which obtains the lowest word error rate on CoRal (2025/11/04). Also exist in a 1B version.
jinaai/jina-embeddings-v3
Feature Extraction • 0.6B • Updated • 2.94M • 1.15kNote Among the best large-sized embedding model with flexible embedding sizes and long-document understanding. Determined by The Scandinavian Embedding Benchmark (SEB) (2025/11/04)
intfloat/multilingual-e5-large-instruct
Feature Extraction • 0.6B • Updated • 1.56M • • 628Note Among the best large-sized embedding model with Instructions. Determined by The Scandinavian Embedding Benchmark (SEB) (2025/11/04)
intfloat/multilingual-e5-large
Feature Extraction • 0.6B • Updated • 8.23M • • 1.21kNote Among the best large-sized embedding model which does not require instructions. Determined by The Scandinavian Embedding Benchmark (SEB) (2025/11/04)
intfloat/multilingual-e5-base
Sentence Similarity • 0.3B • Updated • 6.61M • • 368Note Among the best medium-sized embedding model which does not require instructions. Determined by The Scandinavian Embedding Benchmark (SEB) (2025/11/04)
intfloat/multilingual-e5-small
Sentence Similarity • 0.1B • Updated • 9.98M • • 348Note Among the best small-sized embedding model which does not require instructions. Determined by The Scandinavian Embedding Benchmark (SEB) (2025/11/04)
facebook/seamless-m4t-v2-large
Automatic Speech Recognition • 2B • Updated • 459k • 989Note Machine translation (and other tasks)