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Google LLC (Gemini API)

gemini-3-pro-preview

Gemini 3.1 Pro is the next iteration in the Gemini 3 series of models, a suite of highly capable, natively multimodal reasoning models. As of this model card’s date of publication, Gemini 3.1 Pro is Google’s most advanced model for complex tasks. Geminin 3.1 Pro can comprehend vast datasets and challenging problems from massively multimodal information sources, including text, audio, images, video, and entire code repositories.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window1.0M tokens
Max output66K tokens
API typechat
AddedFeb 19, 2026
Model IDgoogle/gemini-3-pro-preview
Data retentionYes
Used for trainingUnknown
Provider location🌍 Global
Privacy policyGemini API Terms →

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model — check the base model page or the Google LLC (Gemini API) models overview.

Pricing

Input / 1M
$2.00
Output / 1M
$12.00
Cache write / 1M
$4.50
Cache read / 1M
$0.20
Estimated cost
100K input + 10K output$0.32
1M input + 100K output$3.20
10M input + 1M output$32.00

Requesty charges exactly what the upstream provider charges — no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to google/gemini-3-pro-preview.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="google/gemini-3-pro-preview",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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Frequently asked questions

How much does gemini-3-pro-preview cost?
gemini-3-pro-preview is priced at $2.00 per million input tokens and $12.00 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges — we don't add markup.
What is the context window of gemini-3-pro-preview?
gemini-3-pro-preview has a context window of 1.0M tokens, with a maximum output of 66K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
What can gemini-3-pro-preview do?
gemini-3-pro-preview supports vision input, tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use gemini-3-pro-preview with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "google/gemini-3-pro-preview". The Quickstart above shows Python, JavaScript and cURL snippets.

Access gemini-3-pro-preview through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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