
Microsoft Open-Sources Harrier, a New Embedding Leader
Microsoft's Harrier-OSS-v1 family delivers three MIT-licensed multilingual embedding models, with the 27B variant claiming top spot on Multilingual MTEB v2 at 74.3.

Microsoft's Harrier-OSS-v1 family delivers three MIT-licensed multilingual embedding models, with the 27B variant claiming top spot on Multilingual MTEB v2 at 74.3.

Italian-Legal-BERT is a 110M-parameter domain-adapted BERT model for Italian legal NLP, trained on 3.7GB of court decisions from Italy's National Jurisprudential Archive.

Researchers at Scuola Superiore Sant'Anna in Pisa built Italian-Legal-BERT, a 110M-parameter model trained on 3.7GB of Italian court decisions that outperforms general Italian BERT on legal NLP tasks.

Gemini 2.5 Flash Lite leads the Vectara hallucination leaderboard at 3.3% error rate while GPT-4o and Gemini 2.5 Pro dominate long-document tasks - full rankings, benchmark scores, and pricing.

Gemini 2.5 Pro leads WMT25 human evaluation across 16 language pairs while GPT-5 tops community benchmarks - full rankings, BLEU and COMET scores, and pricing for every major model.

Rankings of the best AI models for multilingual tasks, covering 16 languages across the Artificial Analysis Multilingual Index and MGSM benchmarks.

Google Gemma 3 27B is a 27B dense multimodal model supporting text and vision with a 128K context window, 140+ languages, and single-GPU deployment - the most capable open model at its size class.