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gemini-3.5-flash

Gemini 3.5 Flash provides sustained frontier-level intelligence optimized for real-world tasks at a higher speed and lower cost. Designed for the agentic era, it excels at sub-agent deployment, multi-step workflows, and long-horizon tasks at scale.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window1.0M tokens
Max output66K tokens
API typechat
AddedMay 19, 2026
Model IDvertex/gemini-3.5-flash@us
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
$1.50
Output / 1M
$9.00
Cache write / 1M
$1.58
Cache read / 1M
$0.15
Estimated cost
100K input + 10K output$0.24
1M input + 100K output$2.40
10M input + 1M output$24.00

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-3.5-flash@us.

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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-3.5-flash@us",
    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
1.0M ctx$1.50/1M
gemini-3.5-flash
@eu
1.0M ctx$1.50/1M
gemini-3.1-flash-lite
1.0M ctx$0.25/1M
gemini-3.1-flash-lite
@us
1.0M ctx$0.25/1M
gemini-3.1-flash-lite
@eu
1.0M ctx$0.25/1M
kimi-k2
262K ctx$0.60/1M
SWE-Bench 66%

Frequently asked questions

How much does gemini-3.5-flash cost?
gemini-3.5-flash is priced at $1.50 per million input tokens and $9.00 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-3.5-flash?
gemini-3.5-flash 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-3.5-flash do?
gemini-3.5-flash 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-3.5-flash 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-3.5-flash@us". The Quickstart above shows Python, JavaScript and cURL snippets.
What region is this deployment?
This variant of gemini-3.5-flash is deployed in us. Region-specific endpoints matter for data residency, latency to your users, and compliance requirements (GDPR, HIPAA). Other regions for the same model may be listed on the Google LLC (Vertex AI) provider page.

Access gemini-3.5-flash 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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