Apertus Mini consists of 16 small language models that showcase distillation and quantization techniques. Developed by the Swiss AI Initiative, the models are fully open with documented training data, code, weights, and alignment principles, and are designed to comply with EU AI Act requirements by respecting opt-outs, removing PII, and preventing memorization.

Claude for Foundation Models is a Swift package that integrates Claude as a server-side language model within Apple's Foundation Models framework. It conforms to the LanguageModel protocol, allowing it to utilize the same LanguageModelSession API for functionality such as respond(to:), streaming, guided generation, and tool calling, with requests sent directly to the Claude API without Apple's involvement.

Apple is offering lower AI infrastructure costs to attract newer developers, allowing those with fewer than 2 million first-time App Store downloads to use its Foundation Models in Private Cloud Compute without incurring cloud API costs. This initiative provides access to advanced AI capabilities while ensuring strong privacy protections.

Apple announced a new AI architecture built on foundation models developed in collaboration with Google, utilizing technologies from the Gemini family. This architecture is designed to operate on-device and on servers through Apple's Private Cloud Compute infrastructure.

GLM-5V-Turbo is a foundation model designed for multimodal agents, enhancing their capabilities in language reasoning and perception across diverse contexts. The model aims to improve the performance of agents in real-world applications by integrating various modalities.

TimesFM is a pretrained time-series foundation model developed by Google Research for time-series forecasting. The latest model version is TimesFM 2.5, with archived versions 1.0 and 2.0 available, and it can be accessed through the TimesFM Hugging Face Collection and is integrated into BigQuery as an official Google product.

Step 3.5 Flash is an open-source foundation model designed for advanced reasoning and agentic capabilities. Utilizing a sparse Mixture of Experts (MoE) architecture, it activates only 11B of its 196B parameters per token, enabling high intelligence density and real-time interaction.