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Gemini 4 Argon Expands Output to 1 Million Tokens

1 OCTOBER 2026·2 MIN READ·2 SOURCES·Trusted source

Gemini 4 Argon pairs a sharply expanded output limit with introductory token pricing and an Artificial Analysis result matching GPT-6 Astra’s Intelligence Index score.

Gemini 4 Argon Expands Output to 1 Million Tokens

Key takeaways · 3

  • 01

    Assess whether million-token outputs materially simplify workflows that currently require multiple model calls.

  • 02

    Budget for input and output token rates to double after the introductory pricing period.

  • 03

    Evaluate benchmark parity alongside hallucination rates rather than treating one composite index as sufficient.

Output and Pricing

Gemini 4 Argon has a 1 million-token output limit, expanding the maximum output from the 64,000-token limit available in prior models. [1] Initially, Gemini 4 Argon costs $2 per 1 million input tokens and $10 per 1 million output tokens, while the later rates are set to rise to $4 per 1 million input tokens and $20 per 1 million output tokens. [1]

Benchmark and Hallucinations

Artificial Analysis says Gemini 4 Argon in its high configuration matches GPT-6 Astra in its max configuration on the evaluator’s Intelligence Index. [2] In the same Artificial Analysis comparison, Gemini 4 Argon is reported with a 15% hallucination rate, whereas GPT-6 Astra is reported with a 51% hallucination rate. [2] The reported Intelligence Index result is a match between the named configurations, but the reported hallucination rates are 15% for Argon and 51% for Astra. [2]

What it means

Argon’s million-token output ceiling is the clearest practical departure from the 64,000-token limit attributed to prior models, potentially reducing how often unusually long generation tasks must be divided. Its benchmark position is more nuanced: Artificial Analysis places Argon high and GPT-6 Astra max at the same Intelligence Index level, while reporting substantially different hallucination rates. Buyers should therefore examine both configuration-specific quality measurements and the scheduled pricing increase when evaluating the model. What the sources don't address: how Argon’s benchmark and hallucination results translate into reliability across specific production workloads.

Practitioners evaluating Gemini 4 Argon must weigh its expanded output capacity against token prices that are scheduled to double. The Artificial Analysis figures also show why composite intelligence scores and hallucination measurements should be reviewed together.

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How this developed

  1. 1 October 2026

    Gemini 4 Argon Expands Output to 1 Million Tokens

  2. 1 October 2026

    Event created from source cluster.

Sources

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