Gemini 4 Argon
Gemini 4 Argon is Google’s multimodal reasoning model, supporting text, image, and file inputs with configurable reasoning levels.
text + image + video + file → text · made by Google
$2→$10per Mtok in / out
Google · 13 sellers
Sold by 29 ways
| Seller | Lane | Rate |
|---|---|---|
| Google Vertex AI cloud | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-31 |
| Databricks cloud | standard | $2.5per Mtok in$12.5per Mtok out$0.13per Mtok cached$2.5per Mtok cache writeraw.githubusercontent.com · read 2026-10-31 |
| Databricks cloud | priority | $4.5per Mtok in$22.5per Mtok out$0.22per Mtok cachedraw.githubusercontent.com · read 2026-10-31 |
| Nous Research 2 ways | $2per Mtok in$10per Mtok out$0.000002per image$0.1per Mtok cached$0.19per Mtok cache write | |
| Nous Research aggregator | batch | $1per Mtok in$5per Mtok out$0.000001per image$0.05per Mtok cached$0.19per Mtok cache writeinference-api.nousresearch.com · read 2026-10-15 |
| Nous Research aggregator | standard | $2per Mtok in$10per Mtok out$0.000002per image$0.1per Mtok cached$0.19per Mtok cache writeinference-api.nousresearch.com · read 2026-10-15 |
| OpenRouter 8 ways | $2per Mtok in$10per Mtok out$0.000002per image$0.1per Mtok cached$0.19per Mtok cache write | |
| OpenRouter aggregator | batch | $1per Mtok in$5per Mtok out$0.000001per image$0.05per Mtok cached$0.19per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| OpenRouter aggregator | google-ai-studio/flex | $1per Mtok in$5per Mtok out$0.05per Mtok cached$0.094per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| OpenRouter aggregator | standard | $2per Mtok in$10per Mtok out$0.000002per image$0.1per Mtok cached$0.19per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| OpenRouter aggregator | google-ai-studio | $2per Mtok in$10per Mtok out$0.1per Mtok cached$0.19per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| OpenRouter aggregator | google-vertex/global | $2per Mtok in$10per Mtok out$0.1per Mtok cached$0.19per Mtok cache writeopenrouter.ai · read 2026-10-16 |
| OpenRouter aggregator | google-vertex/us | $2.2per Mtok in$11per Mtok out$0.11per Mtok cached$0.19per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| OpenRouter aggregator | google-ai-studio/priority | $3.6per Mtok in$18per Mtok out$0.18per Mtok cached$0.34per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| OpenRouter aggregator | google-vertex/global/priority | $3.6per Mtok in$18per Mtok out$0.18per Mtok cached$0.34per Mtok cache writeopenrouter.ai · read 2026-10-15 |
| AtlasCloud aggregator | standard | $1.6per Mtok in$8per Mtok out$0.08per Mtok cachedapi.atlascloud.ai · read 2026-10-22 |
| GitHub Copilot aggregator | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-31 |
| Google aggregator | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| Requesty aggregatornot on the seller's list today | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| Requesty aggregator | vertex | $2per Mtok in$10per Mtok out$0.1per Mtok cachedrouter.requesty.ai · read 2026-10-15 |
| Vercel AI Gateway aggregator | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedai-gateway.vercel.sh · read 2026-10-15 |
| aihubmix aggregator | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| google-vertex aggregator | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| kilo 0 ways | $2per Mtok in$10per Mtok out$0.1per Mtok cached | |
| kilo aggregatornot on the seller's list today | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| merge-gateway 0 ways | $2per Mtok in$10per Mtok out$0.1per Mtok cached | |
| merge-gateway aggregatornot on the seller's list today | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| nano-gpt 0 ways | $2per Mtok in$10per Mtok out$0.1per Mtok cached | |
| nano-gpt aggregatornot on the seller's list today | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| opencode aggregator | standard | $2per Mtok in$10per Mtok out$0.1per Mtok cachedmodels.dev · read 2026-10-14 |
| Venice AI aggregator | standard | $2.5per Mtok in$12.5per Mtok out$0.12per Mtok cachedmodels.dev · read 2026-10-31 |
| edenai 0 ways | $4per Mtok in$20per Mtok out$0.2per Mtok cached | |
| edenai aggregatornot on the seller's list today | standard | $4per Mtok in$20per Mtok out$0.2per Mtok cachedmodels.dev · read 2026-10-14 |
| llmgateway 0 ways | $4per Mtok in$20per Mtok out$0.2per Mtok cached | |
| llmgateway aggregatornot on the seller's list today | standard | $4per Mtok in$20per Mtok out$0.2per Mtok cachedmodels.dev · read 2026-10-14 |
| llmgateway-providers 0 ways | $4per Mtok in$20per Mtok out$0.2per Mtok cached | |
| llmgateway-providers aggregatornot on the seller's list today | standard | $4per Mtok in$20per Mtok out$0.2per Mtok cachedmodels.dev · read 2026-10-14 |
Measured 46 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 1stof 273 | ARC-AGI-1 (Public Eval) | Score (%) (high) | 99.5 |
| 1stof 60 | Apex agents — Epoch AI | Pass@1 score | 0.824 |
| 1stof 39 | Design Arena · agenticgamedev (agents) | Elo | 1262 |
| 1stof 39 | Design Arena · blender3d (agents) | Elo | 1411 |
| 1stof 326 | GPQA Diamond | mean_score (high) | 96.402 |
| 1stof 93 | Simpleqa verified — Epoch AI | mean_score (high) | 76 |
| 2ndof 35 | Blueprint bench 2 — Epoch AI | Score | 54.447 |
| 2ndof 114 | Design Arena · svg (models) | Elo | 1329 |
| 2ndof 306 | OTIS Mock AIME 2024-2025 | mean_score (high) | 100 |
| 4thof 28 | Ebr bench — Epoch AI | mean_score (high) | 64.762 |
| 4thof 18 | Rli — Epoch AI | Score | 17.08 |
| 4thof 71 | Vending bench 2 — Epoch AI | Score | 13718.158 |
| 5thof 14 | Frontiermath erdos — Epoch AI | mean_score (high) | 1.471 |
| 5thof 21 | Frontierswe — Epoch AI | Score (high) | 54.961 |
| 5thof 235 | Scicode — Epoch AI | Score (high) | 61.806 |
| 6thof 82 | Cursorbench — Epoch AI | Score (high) | 52.9 |
| 6thof 35 | Furniture assembly — Epoch AI | mean_score (high) | 72.5 |
| 6thof 142 | Mystery game puzzles — Epoch AI | mean_score (high) | 64 |
| 6thof 25 | Weirdml v3 — Epoch AI | Score (high) | 20.096 |
| 7thof 84 | Proofbench — Epoch AI | Accuracy | 99 |
| 8thof 235 | Dtbench — Epoch AI | Accuracy (low) | 97.6 |
| 9thof 298 | ARC-AGI-1 (Semi-Private) | Score (%) (high) | 98.5 |
| 9thof 132 | Ale bench — Epoch AI | Performance (high) | 2100.1 |
| 9thof 309 | Arc agi — Epoch AI | Score (medium) | 98.5 |
| 9thof 135 | Webdev arena — Epoch AI | Arena Score (high) | 1679.5 |
| 10thof 282 | ARC-AGI-2 (Public Eval) | Score (%) (high) | 97.08 |
| 10thof 169 | Design Arena · website (models) | Elo | 1315 |
| 11thof 154 | Chess puzzles — Epoch AI | mean_score (high) | 59 |
| 11thof 154 | Design Arena · dataviz (models) | Elo | 1335 |
| 11thof 162 | Design Arena · gamedev (models) | Elo | 1366 |
| 11thof 122 | Frontiermath tiers 1 3 v2 — Epoch AI | mean_score (high) | 85.965 |
| 11thof 56 | Gdp pdf — Epoch AI | GDP.pdf score (high) | 0.284 |
| 11thof 30 | Mirrorcode — Epoch AI | mean_score (high) | 58.889 |
| 12thof 290 | Arc agi 2 — Epoch AI | Score (high) | 91.25 |
| 12thof 46 | Frontiercode — Epoch AI | Main score (medium) | 0.475 |
| 13thof 298 | ARC-AGI-2 (Semi-Private) | Score (%) (high) | 91.25 |
| 13thof 86 | Artificial Analysis · Intelligence Index | Artificial Analysis Intelligence Index (high) | 50 |
| 14thof 150 | Design Arena · 3d (models) | Elo | 1370 |
| 14thof 163 | Design Arena · codecategories (models) | Elo | 1327 |
| 16thof 78 | Frontiermath tier 4 v2 — Epoch AI | mean_score (high) | 78.049 |
| 17thof 41 | Design Arena · spreadsheet (agents) | Elo | 1191 |
| 18thof 157 | Design Arena · uicomponent (models) | Elo | 1332 |
| 19thof 197 | Lmca — Epoch AI | Score (high) | 63.69 |
| 20thof 112 | ARC-AGI-3 (Semi-Private) | Score (%) (low) | 49.79 |
| 36thof 260 | Critpt — Epoch AI | Accuracy (high) | 27.143 |
| 85thof 111 | Vectara Hallucination Leaderboard | Hallucination Rate | 12.1 |
About
Gemini 4 Argon — a text model from Google, sold by 13 companies from $1.6 in and $8 out per million tokens, placed 1st of 326 on GPQA Diamond.
It takes text, images, video and files and returns text, with a context window of 1,048,576 tokens. It was published in October 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 search, reasoning and agents. Thirteen companies sell it. The cheapest is $1.6 in and $8 out per million tokens at AtlasCloud. Beside the standard rate there are faster, batch, separately routed, flex and regional lanes. It has been measured on 46 boards, and stands best at 1st of 326 on GPQA Diamond.
Every current figure
- Maker
- Register
- model
- Takes
- text + image + video + file
- Returns
- text
- Context
- 1,048,576 tokens
- Published
- October 2026
- Knowledge to
- March 2026
- Licence
- not read
- Sellers
- 13
- Price
- $1.6 in and $8 out per million tokens — AtlasCloud
- Boards
- 46
- Best place
- 1st of 326 — GPQA Diamond
Known as 2 names
google/gemini-4-argonvertex/gemini-4-argon