Google

Gemini 4 Argon

Google's reasoning model for code migrations, research and complex workflows.

Long-horizon reasoningtext inputtext output

Run this model

google/gemini-4-argon

Use an endpoint supported by this model.

Get a key for this setup →
Thinking guide →
const response = await fetch('https://api.minirouter.sh/v1/chat/completions', {  method: 'POST',  headers: {    Authorization: `Bearer ${process.env.MINIROUTER_KEY}`,    'Content-Type': 'application/json',  },  body: JSON.stringify({    model: 'google/gemini-4-argon',    messages: [{ role: 'user', content: 'Why is the sky blue?' }],    max_tokens: 1024,  }),}) const data = await response.json()console.log(data.choices[0].message.content)
Read docs →

Start with a text request and an explicit max_tokens limit. Thinking shares that budget. MiniRouter currently supports text input for this model.

Introductory provider pricingCurrent prices include MiniRouter's markup. Google announces $4 input and $20 output per million tokens after its introductory period, without specifying an end date. Reasoning counts as output; final charges follow provider-reported usage. Source ↗

Model overview

Input / 1M
$2.1
All-in MiniRouter rate
Output / 1M
$10.5
All-in MiniRouter rate
Context
1M
1,000,000 tokens
Max output
1M
tokens
DeepSWE v1.1
77.9%
Google-reported
Reasoning
low → high
Three effort levels
Announced
30 Sept 2026
publisher release

Built for the longer task

Bring the whole problem

Pair your instructions with code and source material.

Google-reported evaluations

From code changes to completed workflows.

Three different tests, each with its own scoring and setup. These publisher results do not measure MiniRouter performance.

Publisher evidence

DeepSWE v1.1

Long-horizon software engineering in the mini-swe-agent harness. Google-computed, pass@1 at highest thinking.

Published score

0 to 100%

  • Gemini 4 Argon77.9%
Google performance table ↗ · Evaluation methods ↗
View chart data
DeepSWE v1.1 published result
ModelScore
Gemini 4 Argon77.9%

Publisher evidence

Vals Index

An aggregate across finance, coding, legal and tax work, weighted by each sector's contribution to US GDP. Reported by Google from Vals evaluations.

Published score

0 to 100%

  • Gemini 4 Argon68.9%
Google performance table ↗ · Evaluation methods ↗
View chart data
Vals Index published result
ModelScore
Gemini 4 Argon68.9%

Publisher evidence

AutomationBench

End-to-end business workflows on Zapier's private evaluation set. Publisher-reported; this does not measure MiniRouter routes.

Published score

0 to 100%

  • Gemini 4 Argon51.3%
Google performance table ↗ · Evaluation methods ↗
View chart data
AutomationBench published result
ModelScore
Gemini 4 Argon51.3%
Choose the work

Give it a problem with a finish line.

Argon targets sustained reasoning. Compare it with a smaller model for short extraction or classification, where latency and cost may matter more.
  1. [ 01 ]

    Change a codebase

    Supply the relevant files, constraints and acceptance checks. Review the diff and run your tests before shipping.

  2. [ 02 ]

    Reason across source material

    Ask for evidence tied to supplied text. Verify claims and calculations against the originals.

  3. [ 03 ]

    Complete a multi-step task

    Provide your own tools and stopping conditions. Keep checkpoints for long runs and review consequential actions.

Publisher pricing

Introductory rates. Separate from your live price.

Vercel currently lists $2 input and $10 output per million tokens. Google announces $4 and $20 after the introductory period; its announcement gives no end date.

Introductory · per 1M tokens

Input
$2.00
Cached input
$0.10
Output
$10.00
Vercel catalog ↗ · October 13, 2026. Publisher prices exclude MiniRouter markup; current route prices appear above.
View chart data
Argon introductory publisher prices per million tokens
RateUSD
Input$2.00
Cached input$0.10
Output$10.00
Before a long run

Set a budget, then measure the result.

A large output ceiling is headroom, not a target. Vercel lists 1M context and output limits; each request still needs to fit its route and account limits.
  1. [ 01 ]

    Leave room for the answer

    Thinking consumes output tokens. Use an explicit token limit and compare complete answers, total cost and latency.

  2. [ 02 ]

    Keep continuation explicit

    Vercel describes long-form work across multiple requests. MiniRouter does not automatically extend a request beyond its token limit.

  3. [ 03 ]

    Validate added modalities

    Start with text. MiniRouter currently supports text input for this model.

Route

One route, standard clients.

Authenticate with a MiniRouter bearer key. Caller-provided upstream credentials are not used on this route.
Base URLhttps://api.minirouter.sh/v1
Model IDgoogle/gemini-4-argon
Endpoints/v1/chat/completions/v1/messages/v1/responses
Parametersmax_tokens, temperature, stop, tools, tool_choice, reasoning, include_reasoning
Structured outputNot enforced; a requested format is dropped and the answer is plain text.
ModalitiesInput: text · Output: text

Configured providers. Priority follows the live catalog order.

ProviderPriorityInput / 1MOutput / 1MParametersAccess
vercel
1$2.1$10.5max_tokens, temperature, stop, tools, tool_choice, reasoning, include_reasoningMiniRouter balance

Every model, one key.