[…] Ilia Badeev, head of data science at Trevolution Group, told PYMNTS that his team was still marveling at Gemini 2.5’s 1 million context window when Llama 4 Scout comes along with 10 million. “This is an enormous number. With 17 billion active parameters, we get a ‘mini’ level model (super-fast and super-cheap) but with an astonishingly large context. And as we know, context is king,” Badeev said. “With enough context, Llama 4 Scout’s performance on specific applied tasks could be significantly better than many state-of-the-art models.” Continue reading here. …