Gemini 3 Pro: Google's 1M-context frontier model

Gemini 3 Pro is Google DeepMind's flagship and the only frontier model that ships a 1M+ token context window in production (not beta). It's natively multimodal — text, image, audio, and video inputs in a single API call. Native search grounding via googleSearch tool gives it the freshest training cut among the frontier set. Priced at $2.50 per million input tokens and $10 per million output, it undercuts both GPT-5.5 ($5/$30) and Claude Opus 4.7 ($15/$75). The case for: anything that requires loading a whole codebase, book, or long video. The case against: coding (Claude Sonnet 4.6 still edges it on SWE-bench), agent loops (GPT-5.5's tool-calling remains the most stable in production), and writing nuance (Opus 4.7 has more voice).

Specs

Best at

• Whole-repo or whole-book context — the only production frontier model with native 1M+ context.
• Multimodal pipelines — long video + text + audio in one prompt.
• Real-time information — googleSearch grounding is the freshest in the frontier set.
• Price for the context — $2.50/M input is the cheapest frontier model.

Where it loses

• Coding — Claude Sonnet 4.6 still edges it on SWE-bench refactor tasks.
• Agent tool-calling stability — GPT-5.5 remains the most reliable in long agent loops.
• Writing taste — Opus 4.7 retains more voice on heavy revisions.

Frequently asked questions