language models

Portugal has released Amália, its first national AI model trained specifically for European Portuguese. Built on EuroLLM-9B with 9 billion parameters, the model is fully open-source with weights, datasets, and code published under an open license. The government has committed €5.5m in initial funding through 2027.

Allen Institute for AI researchers conducted token-level analysis comparing their 7B-parameter Olmo 3 transformer and Olmo Hybrid models. The study finds hybrid architectures show a loss gap advantage of 0.04 on content words (nouns, verbs, adjectives) versus 0.02 on function words, while transformers match or exceed hybrids on repeated tokens and closing braces.

NVIDIA released Nemotron-Labs-Diffusion-14B, a 14-billion parameter language model that supports three decoding modes by switching attention patterns during inference. The model achieves 850 tokens per second on GB200 hardware at concurrency 1, representing a 3.3x speed-up over standard autoregressive decoding and outperforming Qwen3-8B-Eagle3 by 2.2x in self-speculation mode.

Qwen has released three models in its Qwen3.6 series: a flagship Max Preview model, a 35B parameter A3B variant, and a 27B parameter base model. All three models are now accessible through OpenRouter's API platform.

OpenAI released GPT-5.5, which completes tasks at the same difficulty level faster than GPT-5.4 while using significantly fewer tokens. The model is available to ChatGPT Plus, Pro, Business, and Enterprise users, with API access delayed due to required safeguards.