Gemini 3.1 Flash Lite Preview

Gemini 3.1 Flash Lite 极低成本档

Model ID: gemini-3.1-flash-lite-preview · Type: chat · Provider: Google

Endpoints: /v1/chat/completions · /v1/messages

Pricing

Input (per 1M tokens)$0.1875 USD
Output (per 1M tokens)$1.125 USD
Cache read (per 1M tokens)$0.01875 USD

Capabilities

from openai import OpenAI

client = OpenAI(api_key="sk-...", base_url="https://api.router.ai/v1")
resp = client.chat.completions.create(
    model="gemini-3.1-flash-lite-preview",
    messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)

FAQ

How much does Gemini 3.1 Flash Lite Preview cost on openbat.ai?

Gemini 3.1 Flash Lite Preview (`gemini-3.1-flash-lite-preview`) is billed per usage at $0.1875/1M in · $1.125/1M out, in USD. Current pricing is always listed at https://openbat.ai/models/gemini-3.1-flash-lite-preview.

How do I call Gemini 3.1 Flash Lite Preview through openbat.ai?

Send a request to https://api.router.ai/v1/v1/chat/completions with the header `Authorization: Bearer <your API key>` and `"model": "gemini-3.1-flash-lite-preview"`. The API is OpenAI-compatible, so any OpenAI SDK works by changing base_url to https://api.router.ai/v1 — no other code change.

Which endpoints does Gemini 3.1 Flash Lite Preview support?

Gemini 3.1 Flash Lite Preview can be called on: /v1/chat/completions; /v1/messages.

What is Gemini 3.1 Flash Lite Preview's context window?

Gemini 3.1 Flash Lite Preview accepts up to 1,048,576 input tokens and can return up to 65,536 output tokens. Requests exceeding the input limit are rejected before reaching the model.

What can Gemini 3.1 Flash Lite Preview do?

Gemini 3.1 Flash Lite Preview supports: vision, function_calling, prompt_caching, audio_input, long_context, cache.

Who makes Gemini 3.1 Flash Lite Preview?

Gemini 3.1 Flash Lite Preview is a chat model from Google, available through the openbat.ai gateway with the same API key as every other model.

Call it through the openbat.ai OpenAI-compatible endpoint (API base: https://api.router.ai/v1). AI agents can discover and call every model on this gateway through MCP (https://mcp.router.ai/mcp) with no manual integration.

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