Google Launches Gemini 3.1 Pro Generally Available on Vertex AI: 2M Token Context, Live Web Search, Enterprise-Grade Grounding

Google made Gemini 3.1 Pro generally available on Vertex AI on April 19—its most capable model now available in production for enterprise AI deployments. The headline feature is a 2-million-token context window (equivalent to reading 1,500 full-length books in a single conversation), enabling use cases that were previously impossible: a legal team can upload an entire contract library and ask the model to identify regulatory risks across all documents in seconds; a data analyst can upload a 100-page dataset documentation and ask complex questions that require cross-referencing multiple sections. Live web search is now native to Gemini 3.1 Pro—responses cite their sources directly from Google Search, updated in real-time. Document-level caching is new: if you're running 1,000 analyses on the same 200-page document, the first request pays full price; the remaining 999 are 90% cheaper because Google caches the document's embedding. Native video understanding at 1 fps (frames per second) means teams can upload video content and ask questions about specific scenes without extracting frames manually. Pricing: $2.50 per million input tokens for on-demand; $0.02 per 1M cached input tokens (game-changing for repetitive workflows). Multimodal: accepts text, images, audio, video, and documents. Regional availability: Vertex AI is available in 30+ regions globally, including Europe (GDPR-compliant) and Asia-Pacific. For enterprise adoption, this is the tipping point: Gemini 3.1 Pro now matches or exceeds Claude Opus 4.7 on coding, reasoning, and instruction-following—eliminating the last technical reason not to migrate. Expect massive enterprise adoption in Q2 2026 as procurement teams consolidate on Google Cloud.