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Google LLC (Vertex AI)

gemini-2.5-flash-image

Google's first hybrid reasoning model which supports a 1M token context window and has thinking budgets. Most balanced Gemini model, optimized for low latency use cases.

👁Vision🧠Reasoning🔧Tool calling⚡Caching🎨Image gen
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Specifications

Context window1.0M tokens
Max output66K tokens
API typechat
AddedSep 20, 2025
Model IDvertex/gemini-2.5-flash-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

Input / 1M
$0.30
Output / 1M
$2.50
Cache write / 1M
$2.50
Cache read / 1M
$0.30
Estimated cost
100K input + 10K output$0.0550
1M input + 100K output$0.55
10M input + 1M output$5.50

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-2.5-flash-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-2.5-flash-image",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Other Google LLC (Vertex AI) models

gemini-3.5-flash
@us
1.0M ctx$1.50/1M
gemini-3.5-flash
1.0M ctx$1.50/1M
gemini-3.5-flash
@eu
1.0M ctx$1.50/1M
gemini-3.1-flash-lite
@us
1.0M ctx$0.25/1M
gemini-3.1-flash-lite
1.0M ctx$0.25/1M
gemini-3.1-flash-lite
@eu
1.0M ctx$0.25/1M

Frequently asked questions

How much does gemini-2.5-flash-image cost?
gemini-2.5-flash-image is priced at $0.30 per million input tokens and $2.50 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-2.5-flash-image?
gemini-2.5-flash-image 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-2.5-flash-image do?
gemini-2.5-flash-image supports vision input, tool calling, extended reasoning, prompt caching, image generation. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use gemini-2.5-flash-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-2.5-flash-image". The Quickstart above shows Python, JavaScript and cURL snippets.

Access gemini-2.5-flash-image through Requesty

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

Get started freeAll Google LLC (Vertex AI) models