Gemini 3.1 Pro Preview

Chat Completions

gemini-3.1-pro-preview

Chat Completions

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, offering stronger software engineering performance, more dependable agent behavior, and more efficient token use across demanding workflows. Built on the multimodal foundation of the Gemini 3 series, it delivers high-accuracy reasoning across text, images, video, audio, and code, supported by a 1M-token context window. The 3.1 update brings clear improvements on SWE benchmarks and in real-world coding scenarios, along with more robust autonomous task execution in structured areas like finance and spreadsheet-driven workflows. Created for advanced development and agentic systems, Gemini 3.1 Pro Preview enhances long-horizon stability and tool coordination while further improving token efficiency. It also adds a new medium thinking mode to better balance cost, speed, and quality. The model shines in agentic coding, structured planning, multimodal analysis, and workflow automation—making it a strong fit for autonomous agents, financial modeling, spreadsheet automation, and other high-context enterprise tasks.

Overview Specifications Activity Performance Uptime Examples

Pricing-50%

Pay-as-you-go rates for this model. More details can be found here.

Input Tokens (1M)

$1.00

Cached Input Tokens (1M)

$0.10

Output Tokens (1M)

$6.00

Capabilities

Input Modalities

TextImageAudioFile

Output Modalities

Text

Supported Parameters

Available parameters for API requests

Max Completion TokensReasoning EffortResponse FormatStopTemperatureTool ChoiceToolsTop PWeb Search Options

Usage Analytics

Token usage of this model on our platform

Throughput

Time-To-First-Token (TTFT)

Code Example

Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.

Basic request example. Ensure API key permissions. For more details, see our documentation.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.naga.ac/v1",
    api_key="YOUR_API_KEY",
)

resp = client.chat.completions.create(
    model="gemini-3.1-pro-preview",
    messages=[
        {"role": "user", "content": "What's 2+2?"}
    ],
    temperature=0.2,
)
print(resp.choices[0].message.content)