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Gemini 4 Carbon Undercuts Rivals on Price

Google's strongest model is now broadly available, though its introductory token pricing doubles at the end of November.

Updated on Nov. 10, 2026 in Artificial Intelligence

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Google released its strongest model, Gemini 4 Carbon, to the public on November 10, though its introductory token pricing doubles at the end of November. AI Illustration. Upload story photo >

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Google released Gemini 4 Carbon to the general public on November 10, 2026, after a two-week preview with select cybersecurity defenders. Google calls it its strongest model; it is available now through the Gemini API, Google AI Studio and Gemini for business, and to Google AI Ultra subscribers in the Gemini app, AI Mode in Search and Antigravity. This is a shipped product, not a research preview.

Why it matters

Google positions Carbon for tasks that stretch a model's intelligence, such as multi-step coding and open-ended scientific research, a market where frontier labs are competing on price as well as capability. The launch came one day after Anthropic's Fable 5.2 and weeks after Google's Argon model, signaling a rapid release cadence among leading labs.

The figures are vendor-published: Google's own benchmarks rank Carbon among the most powerful models on the market, behind Anthropic's Fable 5.2, while the introductory token prices are roughly a fifth of GPT-6 Astra's and a quarter of Fable 5.2's. The source does not report independent benchmark scores, and the introductory price is scheduled to change at the end of November.

The players

Google

Alphabet's search and cloud company, which operates the Gemini model family, Google AI Studio, Antigravity and AI Mode in Search.

Anthropic

AI safety-focused lab whose Fable 5.2 model is the benchmark leader Carbon trails in Google's own comparisons.

OpenAI

Developer of the GPT model series, whose GPT-6 Astra is priced roughly five times higher than Carbon's introductory rate.

The details

Carbon is a large language model that Google says is designed for especially demanding work, such as complex multi-step coding and open-ended scientific research. Google is also previewing a swarm feature on Antigravity, its agentic development platform, which turns a single prompt into a coordinated team of agents that divide and execute subtasks in parallel. Access runs through the Gemini API, where developers pay per token processed, with input and output priced separately.

Timeline

  1. Two weeks before public release, Carbon was made available to select cybersecurity defenders (late October 2026).

  2. Google's Argon model launched in October 2026, last month.

  3. Anthropic launched its Fable 5.2 model on November 9, 2026.

  4. Gemini 4 Carbon rolled out to the general public on November 10, 2026.

  5. Introductory pricing for Carbon is scheduled to double at the end of November 2026.

The Tech Race

Carbon arrives one month after Google's Argon model and one day after Anthropic's Fable 5.2, placing it in a near-simultaneous release cycle among frontier labs. Google's own benchmark positioning puts Carbon behind Fable 5.2, so the competitive contest is now as much about price per token as about top-end capability.

Developers and enterprises can access Carbon now through the Gemini API and Gemini for business, and Google AI Ultra subscribers can use it in the Gemini app, AI Mode in Search and Antigravity. Introductory pricing is $2 per million input tokens and $10 per million output tokens, but that rate doubles at the end of November, and it is not yet clear whether lower-tier subscribers or free users will receive Carbon.

The takeaway

Watch whether Carbon's price doubles as scheduled at the end of November, and whether Google publishes independent benchmark results that confirm its claim of frontier-level performance. Both will show whether the price advantage holds once the introductory period ends.

What happens next

Introductory Carbon pricing is scheduled to double at the end of November 2026, when the introductory period ends.

Further reading

For broader context on how frontier models are competing, read our coverage in the Artificial Intelligence section.

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