Short answer: Gemini 4 Carbon is Google’s strongest model. It became available on November 10, 2026 for long, complex tasks like multi-step coding, scientific research and cybersecurity. Gemini 4 Argon, launched to everyone on October 13, 2026, is still Google’s recommended choice for most software and knowledge work.
Carbon is built on Argon and spends more tokens thinking and checking its work.
In the Gemini app, Carbon is currently for Google AI Ultra subscribers only (from $99.99 a month in the US), while Argon is also included in Google AI Pro ($19.99 a month). On the API, both cost $2/$10 per million input/output tokens until November 30, 2026, then $4/$20.
Checked on November 12, 2026 against Google’s launch posts, the Gemini 4 Carbon developer guide, the DeepMind model card and gemini.google/subscriptions (US prices).
Carbon vs Argon at a glance
| Gemini 4 Argon | Gemini 4 Carbon | |
|---|---|---|
| Public launch | October 13, 2026 | November 10, 2026 |
| Google’s positioning | “Ideal choice for the majority” of coding and knowledge work | For tasks “that test the limits of a model’s intelligence” |
| How it works | Deep reasoning | Based on Argon, uses more tokens and extended verification loops |
| Context | 1M unified input-output tokens (API) | 1M unified input-output tokens (API) |
| Thinking levels | See Argon docs | Low, medium (default), high |
| API price to Nov 30 | $2 / $10 per 1M tokens | $2 / $10 per 1M tokens |
| API price from Dec 1 | $4 / $20 | $4 / $20 |
| Gemini app access | Google AI Pro and Ultra | Google AI Ultra |
| Model ID | gemini-4-argon |
gemini-4-carbon |
Sources: Google: Gemini 4 Carbon is now available, Google: Gemini 4 Argon, Gemini 4 Carbon developer guide, DeepMind model card.
What’s new in Gemini 4 Carbon
1. Built for long-horizon agent work
Google says Carbon is designed to “explore thoroughly, reason deeply, and run extended verification loops.” It ranks #1 on CursorBench 4.0, Perplexity’s WANDR and Zapier’s AutomationBench, at “more than 2X lower cost per task compared to the next best external model,” according to Google.
2. /swarm in Google Antigravity (preview)
Google is previewing /swarm in Antigravity, its agent-first coding platform. /swarm turns one prompt into a coordinated team of agents that you can watch in real time. You can give Carbon the hardest roles, such as architecture, coordination and auditing, and pair it with faster models for the rest. Google’s demos include a 3D game and a 3D reconstruction of an office built from public planning PDFs.
3. Better document and data work
Carbon follows strict formats for spreadsheets, decks and reports. It ranks #2 on the new Multimodal Knowledge Agent (MKA) benchmark, built with Artificial Analysis, at what Google says is more than 6X lower cost per task than the top model.
4. Frontier cybersecurity (for verified defenders)
Through Google’s Fairwind Program, “Carbon for cyber” leads Google’s chosen benchmarks for finding, exploiting and patching vulnerabilities. Public Carbon keeps misuse safeguards on.
5. Safety improvements Google reports
- Blocked 99% of attack trajectories from Google’s adaptive red-team agent in simulated cyberattack tests.
- Per-attempt breach rate of 0.8%, down from 3.1% on Argon.
- Passed 92% of a 375-task agentic honesty benchmark, compared with 70% for Argon.
- A 0% attack success rate on Gray Swan’s indirect prompt-injection benchmark. Google adds that prompt-injection robustness “remains an area for continued improvement.”
How Carbon compares with Claude and GPT
Anthropic’s November 9 launch table for Claude Fable 5.2 includes Gemini 4 Carbon. On those numbers, Carbon leads AutomationBench (53.9%) but trails Fable 5.2 on several coding and computer-use tests:
| Benchmark (Anthropic’s table) | Gemini 4 Carbon | Claude Fable 5.2 | GPT-6 Astra |
|---|---|---|---|
| AutomationBench | 53.9% | 51.4% | 41.4% |
| FrontierSWE v2 | 61.2% | 69.9% | 65.5% |
| OSWorld 2.1 | 81.5% | 89.3% | 79.5% |
| Chartography | 72.5% | 73.4% | 71.0% |
Source: Anthropic. Each company tends to pick benchmarks that suit it, so test models on your own work. Our full guide to Claude Fable 5.2 has the full table.
Pricing: apps vs API
Gemini app plans (US prices, checked Nov 12, 2026)
| Plan | Price | Gemini 4 access |
|---|---|---|
| Free | $0 | Flash-Lite model |
| Google AI Plus | $4.99/month | Flash model, 2x Free usage |
| Google AI Pro | $19.99/month | Gemini 4 Argon, 4x Free usage, entry-level Antigravity limits, 5 TB storage |
| Google AI Ultra | $99.99/month (5x Pro) or $199.99/month (20x Pro) | Highest access to Argon and Carbon, plus Carbon in Antigravity |
Source: gemini.google/subscriptions. Prices vary by country and may include promotions.
API
Both models are $2 per million input tokens and $10 per million output tokens through November 30, 2026, with cached input 95% off. From December 1 the price is $4 / $20. Because Carbon uses more tokens than Argon on the same task, your real bill for Carbon can be higher even at the same price per token.
Which should you use?
| You are… | Best pick | Why |
|---|---|---|
| A student or casual user | Free or AI Pro (Argon) | Argon covers most tasks, and Carbon needs Ultra |
| A professional writing, analysing or coding daily | AI Pro (Argon) | Google says Argon suits most work |
| A developer running long agent jobs | Carbon via API or Ultra + Antigravity | Built for multi-step loops and /swarm |
| A researcher or scientist | Apply for Google’s free 6-month Antigravity access | Google offers free access to selected scientists |
| A security team | Apply to the Fairwind Program | Carbon for cyber is gated |
Is Google AI Ultra worth it?
Probably not for most people. At $99.99 a month it costs five times as much as AI Pro. It’s worth it if you:
- run long coding or research agents most days and want Carbon plus Antigravity’s higher limits,
- keep hitting AI Pro usage limits, or
- want the other Ultra extras and would use them.
If you mainly chat, write and summarise, AI Pro with Argon is the better value. You can always upgrade for a month when you have a big project. For a wider comparison, see ChatGPT vs Gemini, Grok vs Claude vs Gemini and the best Claude alternatives.
How to start with Gemini 4 Carbon
- App users: subscribe to Google AI Ultra, then pick Carbon in the Gemini app’s model menu, or in AI Mode in Search.
- Developers: use
gemini-4-carbonwith a paid Gemini API key in Google AI Studio. The SDKs support it from day one. - Antigravity users (Ultra): select Carbon in the desktop app, CLI or IDE extension, and try
/goalor/swarm. - Migrating code: Google offers a
gemini-api-devskill you can install in your coding agent to help switch models.
Common mistakes
- Using Carbon for quick questions. It’s slower and uses more tokens. Argon or Flash is enough.
- Forgetting the price change on December 1. Budget for $4/$20 per million tokens.
- Trusting benchmark charts alone. Run your own small test.
- Over-sharing data. Check workspace and API data terms before uploading sensitive files.
Trending Gemini 4 Prompts You Can Copy
These are popular, widely shared prompt patterns for everyday use, adapted from community examples on Reddit and X and the advice in Google’s Gemini API prompting guide. Replace the text in [brackets] with your own details. We do not claim any prompt is the “most used”; they are practical starting points.
Summarise this article in 5 bullet points, then list 3 questions I should ask next: [paste text]
Why it works: Fixed output format and a follow-up step keep answers short and useful.
Give me a balanced overview of [topic]: key facts, main debates, and what is still uncertain. Cite sources I can check.
Why it works: Asking for uncertainty and sources discourages overconfident answers.
Explain what this code does line by line, then suggest one improvement: [code]
Why it works: Explanation before changes helps you learn and verify the fix.
Rewrite this email so it is polite, clear and under 120 words: [paste email]
Why it works: A tone, a goal and a word limit give the model clear targets.
What are the strongest arguments for and against [claim]? Steelman both sides.
Why it works: Steelmanning gives fairer, more useful research than a one-sided answer.
Write a [language] function that [task]. Include input validation, comments and 3 test cases.
Why it works: Asking for tests and validation produces more reliable code.
Plan 5 dinners for this week for 2 people, under 30 minutes each, using [ingredients]. Add a shopping list.
Why it works: Constraints (time, people, ingredients) turn a vague ask into a usable plan.
Summarise this report in plain English: 5 key findings, 3 limitations, 1 action for me: [paste]
Why it works: Separating findings from limitations improves critical reading.
I get this error: [error]. Here is the code: [code]. What is the likely cause and the smallest fix?
Why it works: The full error plus code and 'smallest fix' avoids big unnecessary rewrites.
Explain [topic] like I'm a beginner, then give me one real-world example.
Why it works: Setting the audience level controls jargon and depth.
Always check facts, numbers and code before you rely on the output.
Disclaimer: This article is for general informational purposes only and does not constitute legal, financial or tax advice. Laws, pricing and product features (including AI regulations such as GDPR, the EU AI Act and UAE rules) change frequently and vary by country. Verify details with official sources and consult a qualified professional before acting. taxtotech.com is not affiliated with Google.
Gemini 4 Carbon vs Argon FAQ
What is Gemini 4 Carbon?
It’s Google’s strongest Gemini 4 model, released on November 10, 2026, for long-horizon agentic work in coding, knowledge work, science and cybersecurity. It’s based on Gemini 4 Argon.
What is the difference between Gemini 4 Carbon and Argon?
Argon is the recommended model for most tasks. Carbon uses more tokens to reason more deeply and verify its work on the hardest problems.
Is Gemini 4 Carbon free?
No. In the Gemini app it needs Google AI Ultra, and on the API it needs a paid tier.
How much does Gemini 4 Carbon cost on the API?
$2 per million input tokens and $10 per million output tokens until November 30, 2026, then $4 and $20.
What is /swarm in Google Antigravity?
It’s a preview feature that turns one prompt into a coordinated team of AI agents working in parallel, which you can monitor in real time.
What are the best Gemini 4 prompts to try?
Start with clear, specific prompts that set a role, a goal and an output format, such as summaries in bullet points, rewrites with a word limit, or step-by-step plans. See the “Trending Gemini 4 Prompts You Can Copy” section above for copy-ready examples; widely shared patterns work best when you add your own context.
Conclusion
Gemini 4 Carbon is Google’s answer to the hardest agentic and research tasks, with leading results on several workflow benchmarks and a powerful /swarm preview. For everyday work, though, Google itself points you to Argon, which is included in the far cheaper AI Pro plan. Start with Argon, try Carbon on the API or with a one-month Ultra subscription for a specific project, and keep the December 1 price change in mind.
