muapi Logomuapi Logo
muapi Logomuapi Logo

Google Gemini 4 Argon: AI Large Language Models

Run Google Gemini 4 Argon via API: frontier reasoning with 1M context for coding and analysis. Try free — pay per generation, no subscription. Gemini 4 Argon is Google DeepMind's frontier reasoning model with a 1M-token unified context and output window, built for long-horizon coding, knowledge work, and cybersecurity. Accepts text and image input with an optional system prompt. Token-based pricing: $2.00/M input tokens and $10.00/M output tokens.

Interactive model controls

Gemini 4 Argon is Google DeepMind's frontier reasoning model with a 1M-token unified context and output window, built for long-horizon coding, knowledge work, and cybersecurity. Accepts text and image input with an optional system prompt. Token-based pricing: $2.00/M input tokens and $10.00/M output tokens.

📝

Overview

About this model

Gemini 4 Argon is Google DeepMind's frontier reasoning model, built for long-horizon coding, knowledge work, and cybersecurity analysis. It offers a 1M-token unified context and output window, so you can feed in whole codebases, long contracts, or research corpora and get long, structured answers back in a single call. It accepts text plus an optional image and a system prompt. For faster, cheaper everyday chat, see Gemini 3.8 Flash; for the previous Pro tier, see Gemini 3.1 Pro.

1Long-Horizon Coding: Plan, write, and refactor across large repositories using the 1M-token context.
2Knowledge Work: Analyze long reports, contracts, and research papers and produce structured summaries.
3Cybersecurity: Review code and configs for vulnerabilities and draft remediation steps.
4Agent Reasoning: Use as the planner model inside multi-step agents and [workflows](/workflows).
5Visual Q&A: Pass an image_url to ask questions about screenshots, diagrams, or documents.
💰

Pricing & Value

Cost analysis

muapiapp$2.00/M input, $10.00/M output

Token-based billing. Minimum $0.0002 per call.

Fal.aiNot available

No dedicated Gemini 4 Argon endpoint at this time.

ReplicateNot available

No dedicated Gemini 4 Argon endpoint at this time.

** Competitor pricing is estimated based on similar model architectures and usage tiers.

⚙️

Technical Details

Configuration schema

Promptstring

The user message or instruction for the model.

Default ValueReview this design doc and list the three biggest risks with suggested mitigations.
Image URLstring

Optional image URL to include as multimodal input.

Default Valueundefined
System Promptstring

Optional system-level instruction to guide model behavior.

Default ValueYou are a helpful assistant that responds concisely.
📖

Implementation Guide

Developer documentation

How to Use Gemini 4 Argon

  1. Write your prompt: Put the task in prompt. Optionally add system_prompt to set role, tone, or output format.

  2. Add an image (optional): Provide image_url to include an image in the request.

  3. Submit and fetch the result: POST returns a request_id; poll /api/v1/predictions/{request_id}/result or pass a webhook URL.

cURL Example

curl -X POST "https://api.muapi.ai/api/v1/gemini-4-argon" \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Review this design doc and list the three biggest risks.",
    "system_prompt": "You are a staff engineer. Be concise and specific."
  }'
❓

Common Questions

Frequently asked

What is Gemini 4 Argon?

Gemini 4 Argon is Google DeepMind's frontier reasoning model with a 1M-token unified context and output window, aimed at long-horizon coding, knowledge work, and cybersecurity.

How is Gemini 4 Argon priced?

Pricing is token-based at $2.00 per million input tokens and $10.00 per million output tokens, with a minimum charge of $0.0002 per call. Reasoning tokens count as output.

Does Gemini 4 Argon accept images?

Yes. Pass an image_url alongside your prompt to ask questions about a screenshot, diagram, or photographed document.

Can I set a system prompt?

Yes. Use the system_prompt field to control persona, tone, and response format.

How do I get the result?

The endpoint is asynchronous: you receive a request_id immediately, then poll the predictions result endpoint or supply a webhook URL to be notified when the text is ready.

How does Gemini 4 Argon differ from Gemini 3.8 Flash?

Argon is the frontier reasoning tier with a much larger context window, suited to deep multi-step work; Flash is optimized for low-latency, low-cost chat. Both use the same prompt, image_url, and system_prompt fields.