# Google Launches Gemini 3.5 Pro with 2-Million Token Context Window

> Google has released Gemini 3.5 Pro, and its headline feature is sheer memory: a two-million-token context window, which the company says is the largest in production and lets the model hold roughly the equivalent of several long books in view at once. The model shipped July 17 through the Gemini API and Vertex AI, aimed squarely at enterprise workloads. Alongside the bigger window, Google is pushing a new Deep Think reasoning mode for multi-step problems, though it is gated behind a $250 per month Ultra tier that signals how much compute this kind of extended reasoning still costs. The company also claims meaningful gains in code generation and long-horizon tasks over earlier Gemini versions. The context-window arms race matters because it changes what you can do without extra engineering: feed in an entire codebase or archive and ask questions directly. Whether developers actually need two million tokens, or whether it becomes a spec-sheet bragging point, is the open question.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: Google Developers Blog · Published Wednesday, July 22, 2026_

## Wortins' read

Google has released Gemini 3.5 Pro, and its headline feature is sheer memory: a two-million-token context window, which the company says is the largest in production and lets the model hold roughly the equivalent of several long books in view at once. The model shipped July 17 through the Gemini API and Vertex AI, aimed squarely at enterprise workloads. Alongside the bigger window, Google is pushing a new Deep Think reasoning mode for multi-step problems, though it is gated behind a $250 per month Ultra tier that signals how much compute this kind of extended reasoning still costs. The company also claims meaningful gains in code generation and long-horizon tasks over earlier Gemini versions. The context-window arms race matters because it changes what you can do without extra engineering: feed in an entire codebase or archive and ask questions directly. Whether developers actually need two million tokens, or whether it becomes a spec-sheet bragging point, is the open question.

## Source

[Read the full story at Google Developers Blog](https://developers.googleblog.com/en/new-features-for-the-gemini-api-and-google-ai-studio/)

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