On October 23, 2026, Beijing-based Moonshot AI released Kimi K3.1 Pro, the first model in its K3.1 series, featuring a 1-million-token context window

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Global publishers are increasingly challenging artificial intelligence developers using copyrighted material without permission for large language model training under fair-use arguments

Kimi K3.1 Pro is a 2.8-trillion total parameter Mixture-of-Experts model that activates 104 billion parameters across 16 of 896 experts using a Stable LatentMoE framework

Moonshot AI released Kimi K3.1 Pro Highspeed alongside Kimi K3.1 Pro, which runs two to three times faster according to official company statements

Kimi K3.1 Pro builds on the base K3 architecture utilizing Kimi Delta Attention and Attention Residuals, trained with joint reinforcement learning across hundreds of downstream domains

Chinese AI company MiniMax released MiniMax M3.1 Flash on October 19, 2026, featuring 428 billion total parameters, about 23 billion active parameters in a mixture-of-experts architecture, and a 1,000,000-token context window.

MiniMax reported that MiniMax M3.1 Flash operates about three times faster than MiniMax M3, with median output speeds consistently exceeding 170 tokens per second.

MiniMax M3.1 Flash API pricing is set at $0.15 per million input tokens and $0.60 per million output tokens, with cached input reads priced at $0.015 per million tokens.

MiniMax confirmed that an earlier build of MiniMax M3.1 Flash operated anonymously under the name Space Bunny, processing over 200 trillion tokens prior to its official launch.

Meta Platforms Inc. released its Muse Wonder foundation AI model and offers paid subscription tiers ranging from $20 to $200 per month for power users and developers.

MiniMax reported that MiniMax M3.1 Flash can reach peak generation speeds exceeding 200 tokens per second.

The RFD4-Proteina model co-developed by Nvidia and the University of Washington generates both protein sequences and three-dimensional structures.

LiteLLM, developed by BerriAI, provides a shared interface for LLM providers including OpenAI, Anthropic, and Google Gemini, receiving approximately 23 million weekly downloads.

Researchers at Mass General Brigham developed the FAHR-Face artificial intelligence foundation model by training the algorithm on over 40 million facial photographs across diverse ages and ethnic backgrounds.

Mass General Brigham researchers fine-tuned the FAHR-Face foundation model into two complementary tools: FAHR-FaceAge for biological age estimation and FAHR-FaceSurvival for direct cancer survival prediction.

The complaints allege Meta Platforms Inc. operated a book-scanning program called Project Vellum starting around mid-2025 that purchased and scanned physical books to train its Muse Spark and Muse Glimmer AI models.

The authors' complaints allege Meta Platforms Inc. downloaded e-books from pirate shadow libraries, including LibGen, Z-Library, Anna's Archive, and the Books3 dataset, to train its large language models.

Artex was developed by Chinese engineer Li Puhua in July 2026 as a penetration testing tool that automates security assessments using large language models.

Claude Duet is built around Anthropic's flagship Opus 5.5 model and operates via a separate mobile app for iOS and Android as well as claude.ai

Wiz researchers noted that while AI helped identify the ancient PHP vulnerabilities CVE-2026-109618 and CVE-2026-109619, large language models also lower the barrier for attackers to adapt exploits across different server configurations

OpenAI announced on October 21, 2026, that it will make its frontier AI models and Codex coding agent available through Google Cloud's Model Garden and Marketplace in the coming weeks