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Google LLC (Vertex AI)

gemini-3-pro-image

Gemini 3 Pro Image, or Gemini 3 Pro (with Nano Banana), is designed to tackle the most challenging image generation by incorporating state-of-the-art reasoning capabilities. It's the best model for complex and multi-turn image generation and editing, having improved accuracy and enhanced image quality.

VisionReasoningTool callingCachingWeb searchImage gen
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Specifications

Context window1.0M tokens
Max output33K tokens
API typechat
AddedMay 7, 2025
Model IDvertex/gemini-3-pro-image
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US / 🇪🇺 EU
Privacy policyVertex AI Data Governance→

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 (Vertex AI) models overview.

Pricing

Prices updated July 22, 2026
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 vertex/gemini-3-pro-image.

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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="vertex/gemini-3-pro-image",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

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claude-sonnet-5
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claude-sonnet-5
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1M ctx$2.20/1M
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claude-sonnet-5
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Frequently asked questions

How much does gemini-3-pro-image cost?
gemini-3-pro-image 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-image?
gemini-3-pro-image has a context window of 1.0M tokens, with a maximum output of 33K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
What can gemini-3-pro-image do?
gemini-3-pro-image supports vision input, tool calling, extended reasoning, prompt caching, web search, image generation. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use gemini-3-pro-image 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 "vertex/gemini-3-pro-image". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run gemini-3-pro-image through Requesty?
Yes. gemini-3-pro-image runs through Requesty's OpenAI-compatible API, served from Google LLC (Vertex AI). You do not host the model yourself: point base_url at Requesty, set the model to "vertex/gemini-3-pro-image", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access gemini-3-pro-image through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

All Google LLC (Vertex AI) models