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gemini-3.1-flash-liteGoogle

from /1M in$0.13google gemini api
context1.0M66K out
best ttft905msgoogle vertex ai
price spread2.2x6 endpoints
endpoints
6
regions
3
best tok/s
285
api
chat
released
May 2026
eu routing
available

capabilities 6/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

The same weights cost 2.2x more on google vertex ai than on google gemini api. That is what the endpoints table is for.

endpoints

6 / 3 regions
Providers serving gemini-3.1-flash-lite, with pricing and measured performance. Best value in each column is coloured.
#flags
1Google Gemini APIGlobal1.0M$0.13$0.75$0.011.43s285.0zdr
2Google Vertex AIGlobal1.0M$0.13$0.75$0.01905ms239.0-zdr
3Google Gemini APIGlobal1.0M$0.25$1.50$0.021.43s285.0zdr
4Google Vertex AIGlobal1.0M$0.25$1.50$0.02905ms239.0-zdr
5Google Vertex AIeu1.0M$0.28$1.65$0.03905ms239.0-zdr
6Google Vertex AIus1.0M$0.28$1.65$0.03905ms239.0-zdr
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Nov 2
median
986ms2.40s3.82s08-3109-2811-022.32s1.50s
hover the plot for weekly values
time to first token per provider: current value, window low and high, and change across the window
providernowlowhighchange
Google Vertex AI905ms1.43s3.59s+18%
Google Gemini API1.43s1.22s1.50s+23%

median wait before the first token lands. this is the number a user feels, and it moves with provider load through the day.

Lines are steps: each sample is one week of traffic held flat, not a slide from the week before. Click a name in the key to drop it from the plot. Measured through Nov 2.

benchmarks

artificial analysis

no published benchmark scores for this model

call it

model=
gemini-3.1-flash-lite

requesty routes this id across every provider serving gemini-3.1-flash-lite, picking on price and health and failing over automatically. the id stays valid when a provider changes underneath it

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

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

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. 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 7

Which providers serve gemini-3.1-flash-lite?
gemini-3.1-flash-lite is available from 2 providers through Requesty: Google Gemini API, Google Vertex AI. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does gemini-3.1-flash-lite cost?
Pricing starts at $0.13 per million input tokens and $0.75 per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.
Is gemini-3.1-flash-lite open weights?
No. gemini-3.1-flash-lite is a proprietary model from Google, served through Google's own API and licensed cloud platforms.
What is the context window of gemini-3.1-flash-lite?
gemini-3.1-flash-lite supports up to 1.0M tokens of context, with up to 66K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
Which provider is fastest for gemini-3.1-flash-lite?
In recent production traffic through Requesty, Google Vertex AI had the lowest median time to first token (905ms) for gemini-3.1-flash-lite. Latency shifts over time, so Requesty's latency-based routing picks the fastest healthy provider per request automatically.
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 "gemini-3.1-flash-lite" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Should I call gemini-3.1-flash-lite by its managed id or a provider id?
Use the managed id, "gemini-3.1-flash-lite". Requesty picks which of the 2 providers serves each request based on price and health, and fails over when one degrades, so the id keeps working while the routing changes underneath it. There is also an EU-only id, "gemini-3.1-flash-lite@eu", which routes the same way but only through EU-hosted providers. Send a provider id like "google/gemini-3.1-flash-lite:flex" only when you need one specific deployment and want no failover.

more from google 6

Other Google models
modelcontextfrom /Mproviders
gemini-4-argon1.0M$2.001
gemini-3.8-flash1.0M$0.751
gemini-3.7-flash1.0M$0.751
gemini-3.6-flash1.0M$0.382
gemini-3.5-flash-lite1.0M$0.152
gemini-3.1-flash-image131K$0.252

route gemini-3.1-flash-lite through one endpoint

One key for 2 providers on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology

gemini-3.1-flash-lite2 providers6 endpointsfrom $0.13 /1M inctx 1.0Mttft 905msspread 2.2xupdated Nov 2