Gemini 3.6 Flash
Gemini 3.6 Flash delivers higher quality across coding, agentic workflows, and web development with reduced token consumption and fewer model calls compared to previous model iterations.
text + image + video + file → text · made by Google
$0.5→$3per 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Offered at no charge, which is not the same as cheap: a free lane carries a rate limit and can be withdrawn.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.
Available within a subscription 1 plan
Bought by the month. What a plan allows is the half of its price that a rate card cannot carry, so it is printed beside every one.
Sold by 28 ways
| Seller | Lane | Rate |
|---|---|---|
| Google api | free | $0per Mtok in$0per Mtok outai.google.dev · read 2026-09-16 |
| Google 0 ways | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cached | |
| Google apinot on the seller's list today | batch | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cachedai.google.dev · read 2026-08-24 |
| Google Vertex AI cloud | batch | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cachedcloud.google.com · read 2026-08-24 |
| Google Vertex AI cloud | flex | $0.38per Mtok in$1.88per Mtok outraw.githubusercontent.com · read 2026-09-16 |
| Google 0 ways | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cached | |
| Google apinot on the seller's list today | standard | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cachedai.google.dev · read 2026-08-24 |
| Google Vertex AI cloud | standard | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cached$3.75per Mtok out, reasoningcloud.google.com · read 2026-08-24 |
| Google Vertex AI cloud | priority | $1.35per Mtok in$6.75per Mtok out$0.14per Mtok cachedraw.githubusercontent.com · read 2026-09-16 |
| Databricks cloud | standard | $1.88per Mtok in$9.38per Mtok out$0.19per Mtok cached$1.88per Mtok cache writeraw.githubusercontent.com · read 2026-09-16 |
| Requesty 2 ways | $0.34per Mtok in$1.69per Mtok out$0.034per Mtok cached | |
| Requesty aggregatornot on the seller's list today | google flex | $0.34per Mtok in$1.69per Mtok out$0.034per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | vertex flex | $0.34per Mtok in$1.69per Mtok out$0.034per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregator | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cachedrouter.requesty.ai · read 2026-09-15 | |
| Requesty aggregator | vertex | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cachedrouter.requesty.ai · read 2026-09-16 |
| Nous Research 2 ways | $0.75per Mtok in$3.75per Mtok out$0.000001per image$0.075per Mtok cached$0.042per Mtok cache write | |
| Nous Research aggregator | batch | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cached$0.042per Mtok cache writeinference-api.nousresearch.com · read 2026-09-12 |
| Nous Research aggregator | standard | $0.75per Mtok in$3.75per Mtok out$0.000001per image$0.075per Mtok cached$0.042per Mtok cache writeinference-api.nousresearch.com · read 2026-09-12 |
| OpenRouter 9 ways | $0.75per Mtok in$3.75per Mtok out$0.000001per image$0.075per Mtok cached$0.042per Mtok cache write | |
| OpenRouter aggregator | batch | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-24 |
| OpenRouter aggregator | google-ai-studio/flex | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cached$0.021per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | google-vertex/global/flex | $0.38per Mtok in$1.88per Mtok out$0.037per Mtok cached$0.021per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | standard | $0.75per Mtok in$3.75per Mtok out$0.000001per image$0.075per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-24 |
| OpenRouter aggregator | google-ai-studio | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | google-vertex/global | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | google-vertex/us | $0.82per Mtok in$4.12per Mtok out$0.083per Mtok cached$0.042per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | google-ai-studio/priority | $1.35per Mtok in$6.75per Mtok out$0.14per Mtok cached$0.075per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | google-vertex/global/priority | $1.35per Mtok in$6.75per Mtok out$0.14per Mtok cached$0.075per Mtok cache writeopenrouter.ai · read 2026-08-25 |
| ElectronHub aggregator | standard | $0.5per Mtok in$3per Mtok outapi.electronhub.ai · read 2026-09-16 |
| GitHub Copilot aggregator | standard | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cachedmodels.dev · read 2026-09-16 |
| Vercel AI Gateway aggregator | standard | $0.75per Mtok in$3.75per Mtok out$0.075per Mtok cachedai-gateway.vercel.sh · read 2026-08-25 |
| Venice AI aggregator | standard | $0.94per Mtok in$4.69per Mtok out$0.094per Mtok cachedmodels.dev · read 2026-09-16 |
| Inference.net aggregator | standard | $1.5per Mtok in$7.5per Mtok out$0.15per Mtok cachedapi.inference.net · read 2026-09-16 |
Measured 49 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 6thof 32 | AIME 2026 | Accuracy (± 95% CI) | 96.67 |
| 6thof 313 | GPQA Diamond | mean_score (high) | 94.129 |
| 7thof 24 | Blueprint bench 2 — Epoch AI | Score | 31.236 |
| 8thof 92 | Design Arena · asciiart (models) | Elo | 1302 |
| 10thof 80 | Simpleqa verified — Epoch AI | mean_score (high) | 66.2 |
| 11thof 161 | Dtbench — Epoch AI | Accuracy (high) | 95.47 |
| 14thof 152 | Design Arena · dataviz (models) | Elo | 1312 |
| 15thof 162 | Design Arena · website (models) | Elo | 1313 |
| 17thof 150 | Design Arena · uicomponent (models) | Elo | 1317 |
| 17thof 30 | Frontiercode — Epoch AI | Main score | 0.344 |
| 17thof 46 | LMArena · Agent | Net Improvement (%) | 5.94 |
| 18thof 222 | Chess puzzles — Epoch AI | mean_score (low) | 43 |
| 19thof 55 | Design Arena · androidnative (agents) | Elo | 1213 |
| 21stof 40 | Design Arena · agenticgamedev (agents) | Elo | 1180 |
| 21stof 156 | Design Arena · codecategories (models) | Elo | 1305 |
| 21stof 152 | LMArena · Vision | Score (Elo) (high) | 1283 |
| 23rdof 63 | Design Arena · mobileapps (agents) | Elo | 1228 |
| 23rdof 402 | LMArena · Text | Score (Elo) (high) | 1480 |
| 25thof 123 | Lmca — Epoch AI | Score (high) | 44.93 |
| 26thof 147 | Design Arena · 3d (models) | Elo | 1301 |
| 26thof 36 | Design Arena · htmlslides (agents) | Elo | 1152 |
| 26thof 39 | Gdp pdf — Epoch AI | GDP.pdf score | 0.14 |
| 26thof 127 | Mystery game puzzles — Epoch AI | mean_score (high) | 30 |
| 26thof 64 | Proofbench — Epoch AI | Accuracy | 36 |
| 28thof 121 | Webdev arena — Epoch AI | Arena Score (high) | 1538.91 |
| 30thof 106 | Frontiermath tiers 1 3 v2 — Epoch AI | mean_score (high) | 58.947 |
| 32ndof 128 | LMArena · WebDev | Score (Elo) (high) | 1537 |
| 33rdof 62 | Design Arena · webapps (agents) | Elo | 1213 |
| 34thof 64 | Design Arena · fullstack (agents) | Elo | 1190 |
| 35thof 155 | Design Arena · gamedev (models) | Elo | 1285 |
| 36thof 43 | Design Arena · python-pptxslides (agents) | Elo | 1146 |
| 39thof 205 | ARC-AGI-1 (Public Eval) | Score (%) (high) | 96 |
| 40thof 62 | Frontiermath tier 4 v2 — Epoch AI | mean_score (high) | 21.951 |
| 43rdof 290 | OTIS Mock AIME 2024-2025 | mean_score (high) | 94.167 |
| 44thof 184 | Artificial Analysis · Coding Index | Index | 69.2 |
| 47thof 230 | ARC-AGI-1 (Semi-Private) | Score (%) (high) | 91.17 |
| 47thof 168 | Scicode — Epoch AI | Score (high) | 52.662 |
| 49thof 216 | ARC-AGI-2 (Public Eval) | Score (%) (high) | 65.28 |
| 51stof 143 | Artificial Analysis · Agentic Index | Index | 30.2 |
| 51stof 69 | Deepswe — Epoch AI | Pass@1 (high) | 0.467 |
| 52ndof 74 | Cursorbench — Epoch AI | Score (high) | 53.5 |
| 54thof 244 | Arc agi — Epoch AI | Score (high) | 91.167 |
| 54thof 302 | Artificial Analysis · Intelligence Index | Artificial Analysis Intelligence Index | 34 |
| 56thof 170 | Weirdml — Epoch AI | Accuracy (high) | 56.1 |
| 59thof 232 | ARC-AGI-2 (Semi-Private) | Score (%) (high) | 60.42 |
| 62ndof 177 | Critpt — Epoch AI | Accuracy (high) | 10.571 |
| 67thof 227 | Arc agi 2 — Epoch AI | Score (high) | 60.417 |
| 71stof 112 | Ale bench — Epoch AI | Performance (high) | 715.52 |
| 156thof 656 | Epoch capabilities index — Epoch AI | ECI Score (high) | 154.26 |
About
Gemini 3.6 Flash — a text model from Google, sold by 11 companies from $0.5 in and $3 out per million tokens, placed 6th of 313 on GPQA Diamond.
It takes text, images, video and files and returns text, with a context window of 1,000,000 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 $0.5 in and $3 out per million tokens at ElectronHub. Beside the standard rate there are separately routed, batch, flex, faster and regional lanes. It has been measured on 49 boards, and stands best at 6th of 313 on GPQA Diamond.
Every current figure
- Maker
- Register
- model
- Takes
- text + image + video + file
- Returns
- text
- Context
- 1,000,000 tokens
- Published
- July 2026
- Knowledge to
- March 2026
- Licence
- not read
- Sellers
- 11
- Price
- $0.5 in and $3 out per million tokens — ElectronHub
- Boards
- 49
- Best place
- 6th of 313 — GPQA Diamond
Known as 10 names
Gemini 3.6 Flash (high)gemini-3.6-flash_highgemini-3.6-flash-highgemini-3.6-flashgoogle/gemini-3.6-flashgoogle/gemini-3.6-flash:batchgoogle/gemini-3.6-flash:flexvertex/gemini-3.6-flashvertex/gemini-3.6-flash:flexGoogle: Gemini 3.6 Flash (batch)