Pass IndexThe State of AISign in

Gemini 3.5 Flash

Google's latest model, highly optimized for coding proficiency and parallel agentic execution loops.

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

$1.5→$9per Mtok in / out
AtlasCloud · 13 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Offered at no charge, which is not the same as cheap: a free lane carries a rate limit and can be withdrawn.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 34 ways

SellerLaneRate
Google apifree$0per Mtok in$0per Mtok outai.google.dev · read 2026-10-31
Google 0 ways$0.75per Mtok in$4.5per Mtok out$0.075per Mtok cached
Google apinot on the seller's list todaybatch$0.75per Mtok in$4.5per Mtok out$0.075per Mtok cachedai.google.dev · read 2026-08-24
Google Vertex AI cloudbatch$0.75per Mtok in$4.5per Mtok out$0.075per Mtok cachedraw.githubusercontent.com · read 2026-10-31
Google Vertex AI cloudflex$0.75per Mtok in$4.5per Mtok outraw.githubusercontent.com · read 2026-10-31
Databricks cloudstandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cached$1.88per Mtok cache writemodels.dev · read 2026-10-31
Google 0 ways$1.5per Mtok in$9per Mtok out$0.15per Mtok cached
Google apinot on the seller's list todaystandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedai.google.dev · read 2026-08-24
Google Vertex AI cloudstandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cached$1.5per Mtok in, audio$9per Mtok out, reasoningmodels.dev · read 2026-10-31
Google Vertex AI cloudpriority$2.7per Mtok in$16.2per Mtok out$0.27per Mtok cachedraw.githubusercontent.com · read 2026-10-31
Databricks cloudpriority$3.37per Mtok in$20.25per Mtok out$0.34per Mtok cachedraw.githubusercontent.com · read 2026-10-31
Requesty 2 ways$0.68per Mtok in$4.05per Mtok out$0.072per Mtok cached
Requesty aggregatornot on the seller's list todaygoogle flex$0.68per Mtok in$4.05per Mtok out$0.072per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatornot on the seller's list todayvertex flex$0.68per Mtok in$4.05per Mtok out$0.068per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatornot on the seller's list todayvertex eu$1.49per Mtok in$8.91per Mtok out$0.15per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatornot on the seller's list todayvertex us$1.49per Mtok in$8.91per Mtok out$0.15per Mtok cachedrouter.requesty.ai · read 2026-08-25
Requesty aggregatorgoogle$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedrouter.requesty.ai · read 2026-10-10
Requesty aggregatorvertex$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedrouter.requesty.ai · read 2026-10-10
Nous Research 2 ways$1.5per Mtok in$9per Mtok out$0.000002per image$0.15per Mtok cached$0.083per Mtok cache write
Nous Research aggregatorbatch$0.75per Mtok in$4.5per Mtok out$0.000001per image$0.075per Mtok cachedinference-api.nousresearch.com · read 2026-09-12
Nous Research aggregatorstandard$1.5per Mtok in$9per Mtok out$0.000002per image$0.15per Mtok cached$0.083per Mtok cache writeinference-api.nousresearch.com · read 2026-09-12
OpenRouter 9 ways$1.5per Mtok in$9per Mtok out$0.000002per image$0.15per Mtok cached$0.083per Mtok cache write
OpenRouter aggregatorbatch$0.75per Mtok in$4.5per Mtok out$0.000001per image$0.075per Mtok cachedopenrouter.ai · read 2026-08-24
OpenRouter aggregatorgoogle-ai-studio/flex$0.75per Mtok in$4.5per Mtok out$0.075per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-vertex/global/flex$0.75per Mtok in$4.5per Mtok out$0.075per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorstandard$1.5per Mtok in$9per Mtok out$0.000002per image$0.15per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-24
OpenRouter aggregatorgoogle-ai-studio$1.5per Mtok in$9per Mtok out$0.15per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-vertex/global$1.5per Mtok in$9per Mtok out$0.15per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-vertex/us$1.65per Mtok in$9.9per Mtok out$0.17per Mtok cached$0.083per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-ai-studio/priority$2.7per Mtok in$16.2per Mtok out$0.27per Mtok cached$0.15per Mtok cache writeopenrouter.ai · read 2026-08-25
OpenRouter aggregatorgoogle-vertex/global/priority$2.7per Mtok in$16.2per Mtok out$0.27per Mtok cached$0.15per Mtok cache writeopenrouter.ai · read 2026-08-25
AtlasCloud aggregatorstandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedapi.atlascloud.ai · read 2026-09-20
DeepInfra aggregatorstandard$1.5per Mtok in$9per Mtok outapi.deepinfra.com · read 2026-08-25
ElectronHub aggregatorstandard$1.5per Mtok in$9per Mtok outapi.electronhub.ai · read 2026-10-31
GitHub Copilot aggregatorstandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedmodels.dev · read 2026-10-31
Inference.net aggregatorstandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedapi.inference.net · read 2026-10-31
Vercel AI Gateway aggregatorstandard$1.5per Mtok in$9per Mtok out$0.15per Mtok cachedvercel.com · read 2026-08-25
Vercel AI Gateway aggregatornot on the seller's list todaysandbox$1.5per Mtok in$9per Mtok outvercel.com · read 2026-08-25
Venice AI aggregatorstandard$1.55per Mtok in$9.45per Mtok out$0.15per Mtok cached$0.086per Mtok cache writemodels.dev · read 2026-10-31

Measured 64 standings

PlaceBoardMetricScore
3rdof 15Design Arena · agenticslides(python-pptx) (agents)Elo1242
3rdof 13Design Arena · pptxslides (agents)Elo1244
3rdof 35Swe bench verified — Epoch AImean_score (high)79.339
4thof 15Design Arena · agenticslides (agents)Elo1244
4thof 46Enigma eval — Epoch AIAccuracy (high)25.41
6thof 102Simplebench — Epoch AIScore (AVG@5)0.767
8thof 41Design Arena · python-pptxslides (agents)Elo1247
9thof 15Design Arena · agentichtmlslides (agents)Elo1162
9thof 15Design Arena · agenticslides(html) (agents)Elo1162
12thof 35Blueprint bench 2 — Epoch AIScore33.623
12thof 93Simpleqa verified — Epoch AImean_score (high)66.2
14thof 101FrontierMath (Tiers 1-3)mean_score (high)38.966
14thof 23Gbaeval — Epoch AIOverall score0.067
14thof 29Surface evolver bench — Epoch AIMean score (medium)0.581
20thof 72Frontiermath tier 4 — Epoch AImean_score (high)14.583
22ndof 39Design Arena · agenticgamedev (agents)Elo1128
22ndof 165LMArena · VisionScore (Elo) (medium)1285
23rdof 54Design Arena · androidnative (agents)Elo1181
25thof 326GPQA Diamondmean_score (high)92.803
26thof 28Ebr bench — Epoch AImean_score (high)4.762
27thof 114Design Arena · svg (models)Elo1253
28thof 61Design Arena · fullstack (agents)Elo1197
28thof 41Design Arena · spreadsheet (agents)Elo1080
28thof 92Forecastbench — Epoch AIOverall score64.4
28thof 414LMArena · TextScore (Elo) (high)1478
29thof 36Design Arena · htmlslides (agents)Elo1039
30thof 93Design Arena · asciiart (models)Elo1251
30thof 71Vending bench 2 — Epoch AIScore5396.418
31stof 154Chess puzzles — Epoch AImean_score (high)45
31stof 34Design Arena · pdf (agents)Elo1070
33rdof 142Mystery game puzzles — Epoch AImean_score (high)32
35thof 68Design Arena · webapps (agents)Elo1190
36thof 39Design Arena · blender3d (agents)Elo963
38thof 68Design Arena · mobileapps (agents)Elo1176
41stof 122Frontiermath tiers 1 3 v2 — Epoch AImean_score (high)62.807
42ndof 163Artificial Analysis · Coding IndexIndex70.1
42ndof 50Design Arena · godotgamedev (agents)Elo1098
42ndof 56Gdp pdf — Epoch AIGDP.pdf score0.14
45thof 84Proofbench — Epoch AIAccuracy (high)31
46thof 173Weirdml — Epoch AIAccuracy (high)62.64
49thof 157Design Arena · uicomponent (models)Elo1266
49thof 169Design Arena · website (models)Elo1267
50thof 78Frontiermath tier 4 v2 — Epoch AImean_score (high)26.829
51stof 131Artificial Analysis · Agentic IndexIndex26
51stof 150Design Arena · 3d (models)Elo1241
51stof 162Design Arena · gamedev (models)Elo1262
53rdof 163Design Arena · codecategories (models)Elo1265
53rdof 235Dtbench — Epoch AIAccuracy (high)94.67
54thof 141LMArena · WebDevScore (Elo)1509
54thof 306OTIS Mock AIME 2024-2025mean_score (high)95.556
55thof 135Webdev arena — Epoch AIArena Score1506.38
56thof 60Apex agents — Epoch AIPass@1 score0.275
57thof 298ARC-AGI-2 (Semi-Private)Score (%) (high)72.08
58thof 298ARC-AGI-1 (Semi-Private)Score (%) (high)92.5
58thof 69Deepswe — Epoch AIPass@1 (medium)0.374
59thof 273ARC-AGI-1 (Public Eval)Score (%) (high)96
60thof 154Design Arena · dataviz (models)Elo1239
61stof 282ARC-AGI-2 (Public Eval)Score (%) (high)72.08
62ndof 290Arc agi 2 — Epoch AIScore (high)72.08
63rdof 309Arc agi — Epoch AIScore (high)92.5
69thof 132Ale bench — Epoch AIPerformance (high)911.02
73rdof 235Scicode — Epoch AIScore (high)53.935
80thof 197Lmca — Epoch AIScore (high)47.15
105thof 260Critpt — Epoch AIAccuracy (high)13.143

About

Gemini 3.5 Flash — a text model from Google, sold by 13 companies from $1.5 in and $9 out per million tokens, placed 6th of 102 on Simplebench — Epoch AI.

It takes text, images, video and files and returns text, with a context window of 1,048,576 tokens. It was published in May 2026, trained on material up to January 2025. Its sellers say it can reason step by step and call a tool. The catalogue files it under reasoning, code and agents. Thirteen companies sell it. The cheapest is $1.5 in and $9 out per million tokens at AtlasCloud. Beside the standard rate there are faster, separately routed, batch, flex and regional lanes. It has been measured on 64 boards, and stands best at 6th of 102 on Simplebench — Epoch AI.

Every current figure

Maker
Google
Register
model
Takes
text + image + video + file
Returns
text
Context
1,048,576 tokens
Published
May 2026
Knowledge to
January 2025
Licence
not read
Sellers
13
Price
$1.5 in and $9 out per million tokens — AtlasCloud
Boards
64
Best place
6th of 102 — Simplebench — Epoch AI

Known as 13 names

Gemini 3.5 Flash (high)gemini-3.5-flash-highgemini-3.5-flash-mediumgoogle/gemini-3.5-flashgemini-3.5-flashgoogle/gemini-3.5-flash:batchgoogle/gemini-3.5-flash:flexvertex/gemini-3.5-flashvertex/gemini-3.5-flash:flexvertex/gemini-3.5-flash@euvertex/gemini-3.5-flash@usgoogle/gemini-3.5-flash-batchGoogle: Gemini 3.5 Flash (batch)