How much does prompt caching save on Gemini 3.1 Pro preview?

Gemini 3.1 Pro preview supports context caching. Stable prefixes such as system prompts and tool definitions benefit most. Measure your cache-hit ratio before assuming a budget change.

How do you get a cache hit on Gemini 3.1 Pro preview?

Keep the repeated prefix identical at the start of each request. Stable content like system prompts and fixed knowledge are better cache candidates than one-off documents.

Does Gemini 3.1 Pro preview charge more for long inputs?

Gemini 3.1 Pro preview uses a single published rate for input, regardless of request length; see the pricing table for the applicable amount.

Does Gemini 3.1 Pro preview support tool calling and structured output?

Yes. Gemini 3.1 Pro preview supports function calling and structured outputs, enabling reliable tool use and schema-enforced JSON responses.

What should you evaluate before moving production traffic to Gemini 3.1 Pro preview?

Before moving production traffic to Gemini 3.1 Pro preview, verify specs and rate limits, run a pilot, and compare quality, latency, and cost against your current setup.

Model detail

Gemini 3.1 Pro preview

Provided by Google

Pay-as-you-go

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation of the Gemini 3 series, it combines high-precision reasoning across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling. The 3.1 update introduces measurable gains in SWE benchmarks and real-world coding environments, along with stronger autonomous task execution in structured domains such as finance and spreadsheet-based workflows. Designed for advanced development and agentic systems, Gemini 3.1 Pro Preview improves long-horizon stability and tool orchestration while increasing token efficiency. It introduces a new medium thinking level to better balance cost, speed, and performance. The model excels in agentic coding, structured planning, multimodal analysis, and workflow automation, making it well-suited for autonomous agents, financial modeling, spreadsheet automation, and high-context enterprise tasks.

Model specs

Model ID: gemini-3.1-pro-preview

Context length: 1.048576M
Max output: 65.536K
I/O modalities
Released: 2026-02

API endpoints

One MixRoute gateway, OpenAI-compatible

Gemini /v1beta/models/{model}:generateContent POST
OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$2.0000 /1M Tokens

Completion

$12.0000 /1M Tokens

Cache read

$0.2000 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Pro-level thinking and reliability for engineering workflows

Gemini 3.1 Pro preview is built to refine the performance and reliability of the Gemini 3 Pro series, with better thinking, improved token efficiency, and a more grounded, factually consistent experience. Optimized for software engineering, agentic workflows requiring precise tool usage, and reliable multi-step execution across real-world domains.

What should you check before using it?

1,048,576 context, 65,536 output, improved token efficiency

Supports caching, thinking, structured outputs, function calling, code execution, and search grounding. Knowledge cutoff: 2025-01. Released 2026-02.

Why use it through MixRoute?

Drop-in via Google Gen AI SDK or OpenAI-compatible endpoint

Use the Google Gen AI SDK or call through MixRoute's OpenAI-compatible endpoint. Supports batch API, flex inference, and priority inference for production workloads.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

Tool calling

Gemini 3.1 Pro preview supports function and tool calls.

EX Send a tools definition; the response returns tool_calls to execute and feed results back.

Structured output

Gemini 3.1 Pro preview can produce JSON-formatted output on demand.

EX response_format: { type: "json_schema" } forces valid JSON output.

Streaming

Gemini 3.1 Pro preview supports streamed responses.

EX stream: true streams tokens incrementally, so chat UIs render as they arrive.

Prompt caching

Gemini 3.1 Pro preview supports prompt caching under supported routing conditions.

EX Keep the system prompt and tool definitions at the start of the request; repeated prefixes are automatically billed at the cache-read rate.

Vision input

Gemini 3.1 Pro preview can process image inputs alongside text.

EX Pass a base64-encoded image in a image_url content part alongside text messages.

OpenAI SDK

Call Gemini 3.1 Pro preview through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 1.048576M

Output tokens Max per request 65.536K

Requests / month

Cache hit rate 0%

Share of the same prefix read repeatedly, up to 100%

FAQ

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

gemini-3.1-pro-preview

Create an API key

New users get $5 in free credits

Test this model and alternate routes with the same request format

Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.

Create an API key View integration docs