Gemini 3 Pro debuts with a sparse MoE design, 1M‑token context and 64K output, posting leading scores on SWE‑bench, LiveCodeBench and Video‑MMMU. Tiered pricing by prompt length; releases add tool use/function calling, agentic coding, and deep IDE/agent integrations, alongside broad performance gains.
Main Content
Gemini 3 Pro new model release: Ships a sparse Mixture‑of‑Experts (MoE) architecture with a 1M‑token context window and 64K output tokens, a January 2025 knowledge cutoff, stronger multimodal understanding, and leading scores on major benchmarks: SWE‑bench Verified 76.2%, LiveCodeBench Pro Elo 2439, Video‑MMMU 87.6%.
Gemini 3 Pro pricing updates: Tiered pricing by prompt length — ≤200K tokens: input $2 per million tokens, output $12 per million tokens; >200K tokens: input $4 per million tokens, output $18 per million tokens. Access via the Gemini API, Google AI Studio, and Vertex AI.
Gemini 3 Pro feature updates: Adds tool use and function calling, delivering an ≈30% improvement relative to Gemini 2.5 Pro. Supports agentic coding and vibe coding. Integrates Google Search, URL context, and a code‑execution tool with composable structured outputs.
Gemini 3 Pro performance optimization: Achieves HLE 41.0%, GPQA Diamond 93.8%, ARC‑AGI‑2 Verified 45.1%. Improves coding tasks ≈20%, world knowledge ≈15%, screen understanding 6×, and video/image understanding ≈10%.
Gemini 3 Pro integrations: Adds deep integrations with Cursor, GitHub, JetBrains, Cline, and Google Antigravity, enabling agentic CLI, Android Studio, and bash tooling, strengthening multi‑step workflow automation.
Gemini 3 Pro industry collaboration: Works with the Google Antigravity IDE for end‑to‑end task planning, coding, testing, and iteration, with support for Nano Banana and Gemini 2.5 Computer Use agent behaviors.
Gemini 3.0 in Google Colab: Integrates Gemini 3.0 into Google Colab, improving code‑generation accuracy, reasoning depth, and project insights, delivering advanced AI assistance in Python programming environments.
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