Google has released Gemini 3.1 Flash-Lite, positioning it as the fastest and most cost-efficient model in its Gemini 3 series. The release targets deployment scenarios requiring high-speed inference at reduced computational cost.
Google DeepMind has released Gemini 3.1 Flash-Lite, positioning it as the fastest and most cost-efficient model in the Gemini 3 series. The release targets applications requiring high-speed inference at scale, continuing Google's multi-tier model strategy across the Gemini family.
Google DeepMind has released Nano Banana 2, an image generation model that combines advanced world knowledge and subject consistency with faster inference speeds comparable to its Flash offering. The model is positioned as production-ready with capabilities previously associated with Pro-tier performance.
Google's Gemini 3.1 Pro, an agentic coding model optimized for autonomous development workflows, is now available in public preview within GitHub Copilot. The model emphasizes efficient edit-then-test loops and tool use in early testing.
Google DeepMind is pushing for moral behavior in large language models to be evaluated with the same technical rigor applied to coding and math benchmarks. As LLMs take on roles like companions, therapists, and medical advisors, the research group argues current evaluation standards are insufficient.
Google Deepmind has integrated its Lyria 3 model into Gemini, enabling users to generate 30-second music tracks with vocals, lyrics, and cover art from text prompts or uploaded media. The model represents an expansion of Google's multimodal AI capabilities into creative audio generation.
Google announced Gemini 3.1 Pro, positioning the model for complex problem-solving tasks requiring deeper reasoning than previous versions. The release follows Gemini 3 Pro (November 2025) and Gemini 3 Flash (December 2025).