State-of-the-art Danish Models
These models constitute state-of-the-art models for Danish within their respective domain (highlighted below the model).
Updated • 77.6k • 1.35kNote 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 • Updated • 1.63M • • 1.9kNote 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 • Updated • 96k • • 877Note 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 • 144k • • 773Note 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 • Updated • 37.3k • • 693Note 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 • 101 • 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 • 168 • 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 • 23Note Among the best medium-sized encoder for Danish determined by EuroEval Danish NLU (2025/11/04)
ltg/norbert3-small
Fill-Mask • Updated • 377 • 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 • 160 • 7Note 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 • Updated • 6.04M • • 5.43kNote 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 • 225 • 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 • 5.16M • 1.13kNote 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 • 845k • • 608Note 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 • 4.7M • • 1.14kNote 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 • 2.62M • • 337Note 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 • Updated • 2.56M • • 284Note 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 • 58.5k • 959Note Machine translation (and other tasks)