GoogleMultimodal Model

Gemini 3.1 Pro Preview

Google's Gemini 3 frontier reasoning model, refined for factual grounding and precise tool use. Optimized for software engineering and multi-step agentic workflows over a 1M-token context with text, image, audio, video, and PDF input.

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.inference.net/v1",
  apiKey: "<YOUR_API_KEY>",
});

const completion = await openai.chat.completions.create({
  model: "gemini-3.1-pro-preview",
  messages: [
    {
      role: "user",
      content: "What is the meaning of life?"
    }
  ],
  stream: true,
});

for await (const chunk of completion) {
  process.stdout.write(chunk.choices[0]?.delta.content as string);
}

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.inference.net/v1",
  apiKey: "<YOUR_API_KEY>",
});

const completion = await openai.chat.completions.create({
  model: "gemini-3.1-pro-preview",
  messages: [
    {
      role: "user",
      content: "What is the meaning of life?"
    }
  ],
  stream: true,
});

for await (const chunk of completion) {
  process.stdout.write(chunk.choices[0]?.delta.content as string);
}

Prompt caching

Keep the stable system content block byte-identical across calls.
Mark it with cache_control: { "type": "ephemeral" } to set a cache point.
Long prompts are required. As a practical target, use roughly 4,000 stable tokens for Gemini 3.1 Pro Preview or 9,000 for the other listed Gemini models; these are not guaranteed provider minimums.
Check usage.prompt_tokens_details.cached_tokens in the response to confirm cache reads.

{
  "messages": [{
    "role": "system",
    "content": [{
      "type": "text",
      "text": "Stable system content...",
      "cache_control": { "type": "ephemeral" }
    }]
  }]
}

{
  "messages": [{
    "role": "system",
    "content": [{
      "type": "text",
      "text": "Stable system content...",
      "cache_control": { "type": "ephemeral" }
    }]
  }]
}

Related models

Model

InputCache readOutput

Kimi K3

1024K input contextVisionToolsReasoning$3.00 / $15.00

256K input contextTools$0.102 / $0.48

125K input context$0.05 / $0.23

$0.05

$0.23

Schematron V2 Turbo

125K input context$0.03 / $0.15

$0.03

$0.15

Start building with Gemini 3.1 Pro Preview today

Serverless, OpenAI-compatible, and billed per token. No commitments.