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  1. Models
  2. Text
  3. Google

Gemini 4 Argon

Google's Gemini 4 Argon is a flagship reasoning model for complex software engineering, mathematical and scientific problem solving, and multi-step agents. It accepts text, images, audio, video, and PDFs, with tool calling and structured outputs. Its 1,048,576-token context is shared across input, thinking, and output; synchronous output is capped at 65,536 tokens.

  • Reasoning
  • Vision
  • Audio Input
  • Video Input
  • Native PDF input
  • Tool Calling
  • Structured Output

Added Oct 13, 2026

Pricing

Auto routing · per 1M tokens
Input
$2.00
Output
$10.00
Cache read
$0.10
Compare provider prices

Specifications

Context window
1M
Max output
65.5K
Avg output (7d)
1.6K tokens
Longer than 88% of models

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

50.4

Intelligence Index: 50.4
Better than 85% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

77.5%

Better than 99% of models compared

AutomationBench-AA Tasks Completed

Fully completed workflows without guardrail violations

53.1%

Better than 99% of models compared

Harvey LAB-AA v1.1

Legal tasks fully passed without material hallucinations

3.9%

Better than 64% of models compared

AA-Briefcase v1.1

Agentic knowledge work (Elo)

1484 Elo

Better than 83% of models compared

GDPval-AA v2.1

Economically valuable tasks (Elo)

1631 Elo

Better than 91% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

21.8%

Better than 75% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

79.7%

Better than 83% of models compared

MLCR-AA

Medical long-context reasoning

13.9%

Better than 47% of models compared

Reasoning

HLE

Humanity's Last Exam

57.1%

Better than 99% of models compared

CritPt

Research-level physics reasoning

27.1%

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

57.1%

Better than 96% of models compared

SciCode

Python programming for scientific computing

61.8%

Better than 98% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

48.3%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

4.3%

Legacy benchmarks

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

79.7%

Better than 83% of models compared

GDPval-AA (unversioned / legacy)

Economically valuable tasks

56.5%

Last updated Nov 2, 2026

Artificial Analysis

Providers

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Compare Gemini 4 Argon with similar models from the same provider or model family.

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Gemini 3.5 Flash Lite

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Gemini 3.6 Flash

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Google's GA Flash model delivers near-Pro coding and agentic capability at Flash-tier speed and cost, with improved token efficiency over Gemini 3.5 Flash. It is optimized for multi-step orchestration, full-stack code refactoring, general reasoning, and multimodal workflows.

Gemini 3.5 Flash

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Google's speed-focused Gemini Flash model for frontier multimodal intelligence across text, images, audio, video, PDFs, and code. Built for agentic coding, reliable tool use, structured outputs, and long-context workflows. Audio input costs $3.00 per million audio tokens.

Gemini 3.5 Flash Thinking

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Gemini 3.5 Flash with higher thinking enabled for harder reasoning, agentic coding, tool use, multimodal analysis, and long-context workflows. Audio input costs $3.00 per million audio tokens.