Open-source LLMs are closing the gap with proprietary models, offering competitive performance for coding, healthcare, and enterprise tasks. The proliferation of MIT-licensed and national models fuels local deployment.
The new Artificial Analysis Openness Index puts K2 think v2 on top for sharing training data and recipe, above models like DeepSeek that release only weights. For on-prem deployment evaluation, training corpus transparency is crucial: without it, aud...
Grok 4.5 debuts with high API costs and unavailability in the EU until July. Yet xAI’s own chart shows MIT-licensed GLM-5.2 closing in on the proprietary model in SWE Bench Pro. Token efficiency, independent benchmarks, and training on thousands of G...
Meituan has open-sourced LongCat-2.0, a fresh component of China’s homegrown AI stack. The release points to a maturing parallel ecosystem focused on data sovereignty and on-premise deployments, lessening reliance on US cloud vendors.
The Portuguese government has released Amalia, a 9 billion-parameter Large Language Model under an Apache 2.0 license. Available in SFT and DPO variants, it aims to strengthen the country's digital sovereignty. The lack of coding benchmarks doesn't h...
Z.ai has released GLM-5.2, ranking fourth in performance benchmarks, with coding and agentic capabilities close to market leaders. Its cost is a fraction of Anthropic or OpenAI, raising questions about how this will influence deployment choices, espe...
