Gemini 3.1 Pro Preview
Google Generally Available
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...
Context
1M
tokens
Input
$2.00
per MTok
Output
$12.00
per MTok
About
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...
Modalities
Input
Audio file Vision Text Video
Output
Text
Code Examples
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.1-pro-preview",
"messages": [
{ "role": "user", "content": "Explain quantum entanglement in one sentence." }
]
}' API Parameters
| Name | Type | Description |
|---|---|---|
include_reasoning | boolean | Include the model's internal reasoning trace in the response. |
max_tokens deprecated | integer | Deprecated. Use max_completion_tokens. |
reasoning | object | Configuration for extended-thinking / reasoning mode. |
response_format | one of | Constrain output to a JSON schema or an enum (structured outputs). |
seed | integer | Deterministic seed for sampling. Same seed + same prompt produces identical output. |
stop | array | Up to 4 sequences where the API will stop generating tokens. |
structured_outputs | boolean | Enable JSON-schema-constrained output. |
temperature | number | Sampling temperature; higher values produce more random output. 0 is deterministic. |
tool_choice | one of | Controls which (if any) tool is called: "none", "auto", "required", or a specific tool. |
tools | array | List of tools (functions) the model may call. |
top_p | number | Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p. |
Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.