Google: Gemini 4 Argon (batch)

Audio input Video input Text input File input Image input Text output
Author's Description

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...

Key Specifications
Cost
$$$$
Context
1M
Released
Oct 13, 2026
Speed
★★★★
Ability
★★★★★
Reliability
★★★★★
Supported Parameters

This model supports the following parameters:

Top P Seed Structured Outputs Temperature Tool Choice Reasoning Include Reasoning Response Format Tools Max Tokens
Features

This model supports the following features:

Tools Structured Outputs Response Format Reasoning
Performance Summary

Google's Gemini 4 Argon, a flagship reasoning model created on October 13, 2026, demonstrates strong overall performance, particularly excelling in reliability and complex problem-solving. It performs among the faster models, ranking in the 66th percentile for speed across four benchmarks, and offers moderate pricing, positioned at the 39th percentile. A standout feature is its exceptional reliability, achieving a perfect 100% success rate across all benchmarks, indicating minimal technical failures. In terms of specific benchmark performance, Gemini 4 Argon exhibits remarkable accuracy across challenging domains. It achieved 92.0% accuracy in Instruction Following, placing it in the 96th percentile, and an impressive 96.0% in both Coding and Mathematics. Its Reasoning capabilities are particularly noteworthy, achieving a perfect 100.0% accuracy, making it the most accurate model at its price point and among models of similar speed. While its duration for Mathematics was in the 52nd percentile, indicating average speed for that task, its overall speed remains competitive. The model's key strengths lie in its precision in following complex instructions, robust coding knowledge, and unparalleled reasoning abilities, especially for deep mathematical and scientific problems. No significant weaknesses were identified in its performance metrics.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $1
Completion $5
Input Cache Read $0.05
Input Cache Write $0.0938
Internal Reasoning $5
Web Search $14000

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
Google AI Studio
Google AI Studio | google/gemini-4-argon-20261013 1M $1 / 1M tokens $5 / 1M tokens
Google
Google | google/gemini-4-argon-20261013 1M $2 / 1M tokens $10 / 1M tokens
Google AI Studio
Google AI Studio | google/gemini-4-argon-20261013 1M $2 / 1M tokens $10 / 1M tokens
Google
Google | google/gemini-4-argon-20261013 1M $3.6 / 1M tokens $18 / 1M tokens
Google AI Studio
Google AI Studio | google/gemini-4-argon-20261013 1M $3.6 / 1M tokens $18 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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