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gemini-3.5-flash-liteGoogle

from /1M in$0.15google llc (gemini api)
context1.0M66K out
best ttft712msgoogle llc (gemini api)
price spread2.2x5 endpoints
endpoints
5
regions
2
best tok/s
390
api
chat
released
July 2026
eu routing
available

capabilities 6/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

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

endpoints

5 / 2 regions
Providers serving gemini-3.5-flash-lite, with pricing and measured performance. Best value in each column is coloured.
#flags
1Google LLC (Gemini API)Global1.0M$0.15$1.25$0.02712ms226.0zdr
2Google LLC (Vertex AI)Global1.0M$0.15$1.25$0.01902ms390.0-zdr
3Google LLC (Gemini API)Global1.0M$0.30$2.50$0.03712ms226.0zdr
4Google LLC (Vertex AI)Global1.0M$0.30$2.50$0.03902ms390.0-zdr
5Google LLC (Vertex AI)eu1.0M$0.33$2.75$0.03902ms390.0-zdr
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Sep 12
median
489ms4.19s7.89s07-0608-0309-072.34s1.41s
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 LLC (Gemini API)712ms1.11s7.28s-81%
Google LLC (Vertex AI)902ms1.42s2.38s+65%

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 Sep 12.

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
GPQA Diamond83.8
Coding Index49.3
SciCode41.3
Intelligence Index22.7
Humanity's Last Exam18.8
5 evalsmean43.2

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-07-21.

call it

model=
gemini-3.5-flash-lite

requesty routes this id across every provider serving gemini-3.5-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-3.5-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 3.5 Flash-Lite is a high efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi agent workflows.

questions 7

Which providers serve gemini-3.5-flash-lite?
gemini-3.5-flash-lite is available from 2 providers through Requesty: Google LLC (Gemini API), Google LLC (Vertex AI). All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does gemini-3.5-flash-lite cost?
Pricing starts at $0.15 per million input tokens and $1.25 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-3.5-flash-lite open weights?
No. gemini-3.5-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-3.5-flash-lite?
gemini-3.5-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-3.5-flash-lite?
In recent production traffic through Requesty, Google LLC (Gemini API) had the lowest median time to first token (712ms) for gemini-3.5-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-3.5-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-3.5-flash-lite" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Should I call gemini-3.5-flash-lite by its managed id or a provider id?
Use the managed id, "gemini-3.5-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-3.5-flash-lite@eu", which routes the same way but only through EU-hosted providers. Send a provider id like "google/gemini-3.5-flash-lite:flex" only when you need one specific deployment and want no failover.

more from google 6

Other Google models
modelcontextfrom /Mproviders
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gemini-3.7-flash1.0M$0.751
gemini-3.6-flash1.0M$0.382
gemini-3.1-flash-image131K$0.252
gemini-3-pro-image1.0M$1.002
gemini-3.5-flash1.0M$0.752

route gemini-3.5-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-3.5-flash-lite2 providers5 endpointsfrom $0.15 /1M inctx 1.0Mttft 712msspread 2.2xupdated Sep 12