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 • 298k • 1.38kNote 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 • 846k • • 2.01kNote 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 • 37.2k • • 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 • 417k • • 896Note 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 • 93.8k • • 717Note 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 • 630 • 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 • 429 • • 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 • 179Note Among the best medium-sized encoder for Danish determined by EuroEval Danish NLU (2025/11/04)
ltg/norbert3-small
Fill-Mask • Updated • 329 • 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 • 1.67k • 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 • 5.5M • • 6.1kNote 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 • 61 • 7Note 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 • 3.24M • 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 • 2.29M • • 631Note 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 • 7.49M • • 1.24kNote 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 • 7.15M • • 379Note 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 • 15.6M • • 380Note 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 • 297k • 999Note Machine translation (and other tasks)