Google’s Gemini Developer API documentation lists Gemini 3.1 Pro Preview with paid-tier pricing starting at $2 per 1 million input tokens and $12 per 1 million output tokens for prompts up to 200,000 tokens, alongside a 1,048,576-token input limit and a 65,536-token output limit.
Google has listed Gemini 3.1 Pro Preview in its Gemini Developer API documentation with published paid-tier pricing and model limits.
Google AI for Developers’ Gemini API pricing page lists gemini-3.1-pro-preview and gemini-3.1-pro-preview-customtools with paid-tier prices of $2 per 1 million input tokens and $12 per 1 million output tokens for prompts up to 200,000 tokens.
The same Google pricing page also shows higher rates for longer prompts and a batch pricing option of $1 per 1 million input tokens and $6 per 1 million output tokens. That distinction matters for developers comparing headline rates, because the cost depends on prompt length and whether batch processing is used.
PricePerToken, an independent model-pricing catalog, also lists Gemini 3.1 Pro Preview at $2 per 1 million input tokens and $12 per 1 million output tokens. Its catalog entry says it was updated on June 21, 2026, and includes additional comparison fields such as output speed and benchmark figures.
Google’s model page for Gemini 3.1 Pro Preview identifies the API model code as gemini-3.1-pro-preview. It lists a 1,048,576-token input limit and a 65,536-token output limit.
The Google model page also notes a separate gemini-3.1-pro-preview-customtools endpoint. According to the Google pricing page, both the standard preview model and the custom-tools endpoint appear under the same paid-tier pricing structure for the listed token bands.
PricePerToken describes the model as having a 1.0 million-token context window, which is broadly consistent with Google’s documented 1,048,576 input-token limit. The catalog also lists an output speed figure of 136 tokens per second and benchmark fields including GPQA 94.1, but those comparison metrics should be read as catalog-reported values rather than primary Google product documentation.
The most important pricing detail in Google’s published table is that the $2 input and $12 output rates apply to prompts up to 200,000 tokens. Google’s pricing documentation indicates that long-context usage is priced differently, so applications that regularly approach the model’s maximum input window may not match the lower headline rate.
Developers should also distinguish standard API usage from batch usage. Google’s Gemini API pricing page lists batch rates of $1 per 1 million input tokens and $6 per 1 million output tokens, but batch processing is not the same as interactive, low-latency serving.
Because the model name includes “preview,” production teams should also monitor Google’s official model and pricing pages for changes. Preview model availability, limits, and pricing can change over time, and Google’s documentation is the authoritative source for API behavior and billing terms.
This report is based on Google AI for Developers’ Gemini API pricing page, Google AI for Developers’ Gemini 3.1 Pro Preview model page, and PricePerToken’s catalog entry for Gemini 3.1 Pro Preview. Google’s pages provide the primary documentation for model codes, token limits, and official pricing, while PricePerToken provides a third-party catalog view with additional comparison fields.
Google has listed Gemini 3.1 Pro Preview in its Gemini Developer API documentation with published paid tier pricing and model limits.
The same Google pricing page also shows higher rates for longer prompts and a batch pricing option of $1 per 1 million input tokens and $6 per 1 million output tokens.
That distinction matters for developers comparing headline rates, because the cost depends on prompt length and whether batch processing is used.
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