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gemini-3.1-flash-liteGoogle Vertex AI @us

in /1M$0.28input tokens
out /1M$1.65output tokens
context1.0M66K out
median ttft905msmeasured
api
chat
hosting
US
model lab
Google
weights
closed
added
May 2026
model id
vertex/gemini-3.1-flash-lite@us

capabilities 6/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

2 providers serve gemini-3.1-flash-lite. This page is one of them. Compare all endpoints

pricing

no markup
input
$0.28
output
$1.65
cache write
$0.09
cache read
$0.03

worked cost

Estimated cost for three request volumes
volumecost
100K in + 10K out$0.0440
1M in + 100K out$0.44
10M in + 1M out$4.40

Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing

provider price, passed throughper 1M tokens

measured

through Nov 2
median ttft
905ms
median tok/s
239.0
blended /1M
$0.34
cache hit
9.5%

Weekly aggregates from production traffic routed through Requesty to this endpoint. A metric with no qualifying sample is left out rather than filled in. Compare against the other providers

benchmarks

artificial analysis

no published scores for this exact variant. region deployments and highspeed tiers usually share the base model's results

policy

data terms
retention
none
trains on prompts
no
hosted in
US
deployment
us

Terms are the provider's, not Requesty's: routing a request here puts it under them. Vertex AI Data Governance

Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.

quickstart

openai compatible
vertex/gemini-3.1-flash-lite@us

this id pins the google vertex ai deployment, with no routing and no failover. the managed id on the canonical page routes across all 2 providers instead

main.py
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-3.1-flash-lite@us",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models

notes

reference

Gemini 3.1 Flash Lite Preview is the most cost-efficient model in the Gemini family, optimized for high-volume, low-latency tasks. It delivers fast responses with solid quality for everyday use cases including summarization, classification, and simple reasoning.

questions 6

How much does gemini-3.1-flash-lite cost?
gemini-3.1-flash-lite is priced at $0.28 per million input tokens and $1.65 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-3.1-flash-lite?
gemini-3.1-flash-lite has a context window of 1.0M tokens, with a maximum output of 66K tokens per response. That is roughly 1,398 words of input you can fit in a single prompt.
What can gemini-3.1-flash-lite do?
gemini-3.1-flash-lite supports vision input, tool calling, extended reasoning, prompt caching, web search, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use gemini-3.1-flash-lite 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-3.1-flash-lite@us". The quickstart pane shows Python, JavaScript and cURL snippets.
Can I run gemini-3.1-flash-lite through Requesty?
Yes. gemini-3.1-flash-lite runs through Requesty's OpenAI-compatible API, served from Google Vertex AI in us. You do not host the model yourself: point base_url at Requesty, set the model to "vertex/gemini-3.1-flash-lite@us", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
What region is this deployment?
This variant of gemini-3.1-flash-lite is deployed in us. Region-specific endpoints matter for data residency, latency to your users, and compliance requirements such as GDPR and HIPAA. Other regions for the same model are listed on the canonical model page.

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call gemini-3.1-flash-lite through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology

gemini-3.1-flash-litegoogle vertex aiin $0.28 /1Mout $1.65 /1Mctx 1.0Mttft 905mshosted US2 providers serve this model