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Gemini 3.5 Flash-Lite

Gemini 3.5 Flash Lite features upgraded agentic capabilities, making the model ideal for subagents in complex workflows.

text + image + video + file → text · made by Google

$0.3→$2.5per Mtok in / out
ElectronHub · 11 sellers

Free

Offered at no charge, which is not the same as cheap: a free lane carries a rate limit and can be withdrawn. The prices above are what you pay when it is not available to you.

Sold by 29 ways

SellerLaneRate
Google apifree$0per Mtok in$0per Mtok outai.google.dev · read 2026-10-31
Google 0 ways$0.15per Mtok in$1.25per Mtok out$0.02per Mtok cached
Google apinot on the seller's list todaybatch$0.15per Mtok in$1.25per Mtok out$0.02per Mtok cachedai.google.dev · read 2026-08-24
Google Vertex AI cloudbatch$0.15per Mtok in$1.25per Mtok out$0.015per Mtok cachedraw.githubusercontent.com · read 2026-10-31
Google Vertex AI cloudflex$0.15per Mtok in$1.25per Mtok outraw.githubusercontent.com · read 2026-10-31
Google 0 ways$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cached
Google apinot on the seller's list todaystandard$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cachedai.google.dev · read 2026-08-24
Google Vertex AI cloudstandard$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cached$2.5per Mtok out, reasoningmodels.dev · read 2026-10-31
Databricks cloudstandard$0.37per Mtok in$3.13per Mtok out$0.038per Mtok cached$0.37per Mtok cache writeraw.githubusercontent.com · read 2026-10-31
Google Vertex AI cloudpriority$0.54per Mtok in$4.5per Mtok out$0.054per Mtok cachedraw.githubusercontent.com · read 2026-10-31
Databricks cloudpriority$0.68per Mtok in$5.62per Mtok out$0.067per Mtok cachedraw.githubusercontent.com · read 2026-10-31
Requesty 2 ways$0.14per Mtok in$1.12per Mtok out$0.018per Mtok cached
Requesty aggregatornot on the seller's list todaygoogle flex$0.14per Mtok in$1.12per Mtok out$0.018per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatornot on the seller's list todayvertex flex$0.14per Mtok in$1.12per Mtok out$0.013per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatornot on the seller's list todayvertex eu$0.3per Mtok in$2.48per Mtok out$0.03per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatorgoogle$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cachedrouter.requesty.ai · read 2026-10-10
Requesty aggregatorvertex$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cachedrouter.requesty.ai · read 2026-10-08
Nous Research 2 ways$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cached$0.083per Mtok cache write
Nous Research aggregatorbatch$0.15per Mtok in$1.25per Mtok out$0.015per Mtok cachedinference-api.nousresearch.com · read 2026-09-12
Nous Research aggregatorstandard$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cached$0.083per Mtok cache writeinference-api.nousresearch.com · read 2026-09-12
OpenRouter 8 ways$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cached$0.083per Mtok cache write
OpenRouter aggregatorbatch$0.15per Mtok in$1.25per Mtok out$0.015per Mtok cachedopenrouter.ai · read 2026-08-24
OpenRouter aggregatorgoogle-ai-studio/flex$0.15per Mtok in$1.25per Mtok out$0.015per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-vertex/global/flex$0.15per Mtok in$1.25per Mtok out$0.015per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorstandard$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-24
OpenRouter aggregatorgoogle-vertex/eu$0.33per Mtok in$2.75per Mtok out$0.033per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-27
OpenRouter aggregatorgoogle-vertex/us$0.33per Mtok in$2.75per Mtok out$0.033per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-ai-studio/priority$0.54per Mtok in$4.5per Mtok out$0.054per Mtok cached$0.15per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-vertex/global/priority$0.54per Mtok in$4.5per Mtok out$0.054per Mtok cached$0.15per Mtok cache writeopenrouter.ai · read 2026-08-25
ElectronHub aggregatorstandard$0.3per Mtok in$2.5per Mtok outapi.electronhub.ai · read 2026-10-31
Inference.net aggregatorstandard$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cachedapi.inference.net · read 2026-10-31
RedPill aggregatorstandard$0.3per Mtok in$2.5per Mtok outapi.redpill.ai · read 2026-09-20
Vercel AI Gateway aggregatorstandard$0.3per Mtok in$2.5per Mtok out$0.03per Mtok cachedai-gateway.vercel.sh · read 2026-08-25
Venice AI aggregatorstandard$0.38per Mtok in$3.12per Mtok out$0.037per Mtok cachedmodels.dev · read 2026-10-31

Measured 28 standings

PlaceBoardMetricScore
40thof 165LMArena · VisionScore (Elo)1266
51stof 56Gdp pdf — Epoch AIGDP.pdf score (high)0.1
55thof 60Apex agents — Epoch AIPass@1 score0.293
66thof 84Proofbench — Epoch AIAccuracy13
69thof 142Mystery game puzzles — Epoch AImean_score (low)19
70thof 414LMArena · TextScore (Elo)1455
72ndof 135Webdev arena — Epoch AIArena Score1446.62
73rdof 141LMArena · WebDevScore (Elo)1440
76thof 78Frontiermath tier 4 v2 — Epoch AImean_score (high)0
77thof 86Artificial Analysis · Intelligence IndexArtificial Analysis Intelligence Index12
81stof 131Artificial Analysis · Agentic IndexIndex14.3
83rdof 122Frontiermath tiers 1 3 v2 — Epoch AImean_score (high)25.965
85thof 132Ale bench — Epoch AIPerformance (high)765.27
86thof 163Artificial Analysis · Coding IndexIndex49.3
92ndof 154Chess puzzles — Epoch AImean_score (low)21
112thof 326GPQA Diamondmean_score (high)83.333
116thof 235Dtbench — Epoch AIAccuracy (high)83.47
116thof 197Lmca — Epoch AIScore (high)37.6
121stof 173Weirdml — Epoch AIAccuracy (high)39
143rdof 306OTIS Mock AIME 2024-2025mean_score (high)71.111
161stof 273ARC-AGI-1 (Public Eval)Score (%) (high)66.38
162ndof 282ARC-AGI-2 (Public Eval)Score (%) (high)7.92
170thof 298ARC-AGI-2 (Semi-Private)Score (%) (high)10.28
172ndof 235Scicode — Epoch AIScore41.319
173rdof 290Arc agi 2 — Epoch AIScore (high)10.278
190thof 298ARC-AGI-1 (Semi-Private)Score (%) (high)53.5
200thof 309Arc agi — Epoch AIScore (high)53.5
217thof 260Critpt — Epoch AIAccuracy0

About

Gemini 3.5 Flash-Lite — a text model from Google, sold by 11 companies from $0.3 in and $2.5 out per million tokens, placed 70th of 414 on LMArena · Text.

It takes text, images, video and files and returns text, with a context window of 1,048,576 tokens. It was published in July 2026, trained on material up to March 2026. Its sellers say it can reason step by step and call a tool. The catalogue files it under reasoning, code and agents. Eleven companies sell it. The cheapest is $0.3 in and $2.5 out per million tokens at ElectronHub. Beside the standard rate there are faster, separately routed, batch, flex and regional lanes. It has been measured on 28 boards, and stands best at 70th of 414 on LMArena · Text.

Every current figure

Maker
Google
Register
model
Takes
text + image + video + file
Returns
text
Context
1,048,576 tokens
Published
July 2026
Knowledge to
March 2026
Licence
not read
Sellers
11
Price
$0.3 in and $2.5 out per million tokens — ElectronHub
Boards
28
Best place
70th of 414 — LMArena · Text

Known as 9 names

gemini-3.5-flash-litegoogle/gemini-3.5-flash-litegoogle/gemini-3.5-flash-lite:batchgoogle/gemini-3.5-flash-lite:flexvertex/gemini-3.5-flash-litevertex/gemini-3.5-flash-lite:flexvertex/gemini-3.5-flash-lite@eugoogle/gemini-3.5-flash-lite-batchGoogle: Gemini 3.5 Flash Lite (batch)