# Gemini 4 Argon: Access, API Pricing, Benchmarks & Limits > Gemini 4 Argon explained: who can use it (AI Pro and Ultra), API pricing before and after December 1, benchmarks, usage limits and how it compares to Carbon. - Published: 2026-11-08 - Updated: 2026-11-08 - Author: Samy BEN SADOK - Canonical: https://geotoolbox.ai/blog/gemini-4-argon --- Gemini 4 Argon is Google's most capable generally available AI model, released on October 13, 2026. You can use it in the Gemini app and AI Mode with a Google AI Pro or Ultra plan, or on the API as `gemini-4-argon` at $2 input and $10 output per million tokens through November 30, 2026, then $4 and $20 from December 1. It is not in the free or AI Plus plans, has no free API tier, and is no longer Google's top model: Gemini 4 Carbon, announced on October 28, ranks higher but is limited to a small group of cyber defenders. Last verified November 8, 2026. ## Gemini 4 Argon at a Glance Specs and access rules from Google's own pages, captured November 8, 2026. The API price is the line most likely to change, on December 1.
ItemGemini 4 Argon
MakerGoogle DeepMind
AnnouncedSeptember 30, 2026 (Fairwind preview for cyber defenders)
Generally availableOctober 13, 2026
API model IDgemini-4-argon
Gemini appGoogle AI Pro ($19.99/month) and Google AI Ultra (from $99.99/month); not Free or AI Plus
AI Mode in SearchAI Pro and Ultra subscribers aged 18+, in select countries, with daily limits
Google AntigravityPaid AI Pro plans and Ultra; not Free or Plus
API price through Nov 30, 2026$2 input / $10 output per 1M tokens
API price from Dec 1, 2026$4 input / $20 output per 1M tokens
Free API tierNone
Context window1,048,576 tokens (input and output combined)
Max output65,536 tokens by default, up to 1,048,576 with long decode
Thinking levelsLow, medium, high (default medium on the API, low in the Gemini app)
Knowledge cutoffMarch 2026
## What Is Gemini 4 Argon? Gemini 4 Argon is Google DeepMind's frontier model and the first release of the Gemini 4 generation. Google built it for long, hard work, according to its [September 30 announcement](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/): real-world software engineering, legal and finance tasks, and cyber defense. It reached the public in stages: 1. **September 30, 2026:** announced as a preview for cyber defenders in Google's Fairwind Program. Google's GA post says Fairwind members can still get Argon "without cyber guardrails"; the public version keeps them. 2. **October 13, 2026:** [made globally available](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/) on the API, in the Gemini app for AI Pro and Ultra subscribers, and in AI Mode in Search. That two-week gap is why some coverage still describes Argon as unveiled but not yet released. It was written between September 30 and October 13, and one such headline was still in Google's results for "gemini 4 argon" on November 8. Argon sits above Gemini 3.1 Pro and the Flash models in Google's lineup, and below Gemini 4 Carbon. On the Google AI Pro plan, Argon now appears next to "our Pro model" (3.1 Pro), which is still available, so you get both. Free users get a Flash-Lite model, and AI Plus gets a Flash model. For the full picture of how these tiers fit, see our guide to [Google's Gemini lineup](https://geotoolbox.ai/blog/what-is-gemini).
![Google's Gemini lineup in November 2026, from Flash-Lite up to Gemini 4 Carbon, with who can use each model](/blog/gemini-4-argon/gemini-lineup-argon-carbon-ladder.png)
Google's Gemini lineup and who can use each model, November 8, 2026. Sources: Google's plans page, Gemini API docs and the Carbon announcement.
**One naming trap:** there is no "Gemini 4 Pro." People search for it because earlier generations had a Pro model, but the Gemini 4 generation uses element names, Argon and then Carbon. The model still called "Pro" in Google's apps is Gemini 3.1 Pro. **Argon vs Gemini 3.1 Pro.** On the [Gemini API](https://aistudio.google.com/docs/pricing), 3.1 Pro (still a preview model) costs $2 input and $12 output per million tokens for prompts up to 200K tokens, and $4 and $18 above that. Argon has no long-prompt surcharge. Through November 30 it costs the same or less than 3.1 Pro at every prompt length; from December 1 it costs more at every prompt length (above 200K tokens the input rate is the same $4; output is $20 vs $18). Argon's knowledge cutoff is March 2026, per the [Gemini 4 model card](https://deepmind.google/models/model-cards/gemini-4-argon/), so it will not know about later events unless it searches. It also has low, medium and high thinking levels, which change both answer quality and how fast you use up your limits. ## Is Gemini 4 Argon Free? Who Can Use It No. Gemini 4 Argon is not free in the Gemini app, in AI Mode, or on the API. The cheapest way in is the Google AI Pro plan at $19.99 a month in the US, per [Google's plans page](https://gemini.google/us/subscriptions/). The Free and AI Plus ($4.99) plans do not include it. Access depends on your plan and on where you use it. The matrix below is for a US account on November 8, 2026.
Plan (US price)Gemini appAI Mode in SearchGoogle Antigravity
Free ($0)No (Flash-Lite model)NoNo
AI Plus ($4.99/month)No (Flash model)NoNo
AI Pro ($19.99/month)YesYes, 18+, daily limitYes, paid plans, entry rate limits
AI Ultra ($99.99 or $199.99/month)Yes, highest accessYes, 18+, daily limitYes, higher or highest rate limits
The API is separate from these plans. Google's [Gemini API pricing page](https://aistudio.google.com/docs/pricing) states that "Gemini 4 Argon is not available on the Free tier," so developers pay per token from the first call. **Antigravity changed after launch.** On October 13, Google's GA post listed Antigravity access for AI Ultra subscribers only. Antigravity's [model documentation](https://antigravity.google/docs/models) now lists AI Pro too, with a footnote: "Available with paid Google AI Pro plans or on trial with eligible premium devices." On Google's developer forum, users on [carrier-bundled](https://discuss.ai.google.dev/t/subject-gemini-4-argon-unavailable-on-jio-google-ai-pro/189886) and [family-shared](https://discuss.ai.google.dev/t/gemini-4-argon-unavailable-for-paid-google-ai-pro-family-members-only-claude-4-6-available/189933) Pro plans report Argon showing as "Unavailable" in Antigravity, and [some directly billed Pro subscribers](https://discuss.ai.google.dev/t/active-paid-google-ai-pro-shows-antigravity-starter-quota-on-app-2-29-0/198730) report a similar problem. **AI Mode is not available everywhere.** Google's [AI Mode help page](https://support.google.com/websearch/answer/16011537) limits Argon to AI Pro and Ultra subscribers aged 18 and over, signed in with a personal account, in a list of supported countries. The list includes the US, the UK and Switzerland, but no European Union member state. You pick Argon from the menu in the "Ask anything" bar; otherwise AI Mode keeps using its default model. **There are two narrow exceptions.** Antigravity's footnote also covers trials on eligible premium devices, and Google is giving the highest Antigravity usage tier to 10,000 scientists for 6 months, subject to eligibility, capacity and selection, per its [GA post](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/). To compare plan prices across the whole Gemini range, see our [Gemini pricing breakdown](https://geotoolbox.ai/blog/gemini-pricing). ## Usage Limits: Why Argon Runs Out Fast on AI Pro One of the most common complaints about Argon is not about quality. It is how quickly it uses up the Gemini app's limit on the AI Pro plan. Google does not publish a message count. Its [plans page footnote](https://gemini.google/us/subscriptions/) says limits are "compute-based" and "factor in the complexity of your prompt, the features you use, and the length of your chat." The limit "refreshes every 5 hours until you reach your weekly limit." AI Pro gets 4x the usage of the free plan, and AI Ultra gets 5x or 20x the usage of AI Pro, depending on the tier. Because the meter counts compute, a heavy model on a high thinking level drains it far faster than a Flash model. Pro subscribers have posted what that looks like in practice: - "Literally let it print 'This is a test' and used 2% of my 5 hour limit," wrote the author of [a 582-upvote r/GeminiAI thread](https://www.reddit.com/r/GeminiAI/comments/1xd6kze/whats_wrong_with_argons_usage_limit) in late October. - Another Pro user in the same thread said one short stock-market question on high thinking "used 100% of my fresh 5 hour usage limit." These are reported experiences, not measurements, and other users in the same threads report milder usage. They still match the mechanism Google describes. The first lever is the thinking level. Argon offers low, medium and high. On the API and on Google Cloud, [medium is the default](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/4-argon); in the Gemini app, Google's [help page](https://support.google.com/gemini/answer/18648722) says it defaults to low if you do not choose. The same page says "higher thinking levels require more of your usage," so keeping high for the hard questions should help a Pro allowance last longer, though by how much depends on the task. One of the most-upvoted replies in that thread was simply "switch from high to medium." AI Mode has its own meter. Google's help page says Argon in AI Mode "has daily usage limits," and when you reach yours you either wait for it to refresh or upgrade. If you regularly hit the cap on Pro, drop the thinking level, move routine work to a lighter model (Gemini 3.1 Pro or a Flash model, both included on Pro), buy AI credits, which the plans page says extend your limits, or pay for Ultra. Developers can skip the app limits entirely and pay per token on the API. ## Gemini 4 Argon API Pricing (and the December 1 Price Change) Gemini 4 Argon launched on the API at an introductory price that ends on November 30, 2026. From December 1, 2026, the standard rate of $4 input and $20 output per million tokens applies, double the launch price. Google's [pricing table](https://aistudio.google.com/docs/pricing) already shows both rates side by side.
Per 1M tokens (USD)Through Nov 30, 2026From Dec 1, 2026
Input (Standard)$2.00$4.00
Output, including thinking tokens (Standard)$10.00$20.00
Cached input (Standard)$0.10$0.20
Input (Batch or Flex)$1.00$2.00
Output (Batch or Flex)$5.00$10.00
Input (Priority)$3.60$7.20
Output (Priority)$18.00$36.00
Three billing details matter more than the headline rate: - **Thinking tokens are billed as output.** The output price explicitly includes them, so a high thinking level raises your bill as well as your latency. - **Context caching is implicit only.** Google's [pricing page](https://aistudio.google.com/docs/pricing) notes that explicit caching is not supported for Argon, so you cannot pin a prompt prefix; you get the discount when the system detects a repeat. - **Search grounding is extra.** It includes 5,000 free requests a month, shared across Gemini 3 and newer models, then $14 per 1,000, with a daily cap of 1,500 requests. A quick worked example: an app that sends 10 million input tokens and receives 2 million output tokens a month pays $40 at the introductory rate ($20 + $20). From December 1, the same traffic costs $80. If your budget was set in October, plan for that.
![Bar chart of API list prices per million tokens: Gemini 4 Argon introductory vs from December 1, 2026, next to Claude Opus 5.5 and GPT-6.1 Sol](/blog/gemini-4-argon/gemini-4-argon-api-price-dec-1-chart.png)
Standard API list prices per million tokens, captured November 8, 2026, from the Google, Anthropic and OpenAI pricing pages.
Against rivals, Argon moves from GPT-6.1 Sol's price point to Claude Opus 5.5's. Through November 30 it costs the same $2/$10 as [GPT-6.1 Sol](https://developers.openai.com/api/docs/pricing) for prompts up to 272K input tokens; OpenAI charges more above that, while Argon keeps one rate across its whole window. From December 1 it matches [Claude Opus 5.5](https://platform.claude.com/docs/en/about-claude/pricing) at $4/$20. List price understates the cost, because Argon uses a lot of tokens. [Artificial Analysis](https://artificialanalysis.ai/models/gemini-4-argon) reports that Argon on high used 113 million tokens to run its Intelligence Index, against a median of 72.6 million, and calls it "notably slow": 27.7 minutes per task against a 12.6-minute median. Artificial Analysis prices Argon at the $4/$20 standard rate, which puts Argon (high) at $9.95 per task on its [leaderboard](https://artificialanalysis.ai/leaderboards/models). That is about the same as Claude Opus 5.5 at max effort ($10.04), its best-scoring setting, and far above Opus 5.5 on high ($3.46). At the introductory $2/$10 rate, the same token use would cost roughly half. For a closer look at per-token math across every Gemini model, see our [Gemini API pricing guide](https://geotoolbox.ai/blog/gemini-api-pricing) and our explainer on [what AI tokens actually cost](https://geotoolbox.ai/blog/ai-token-cost). ## How Good Is Gemini 4 Argon? Benchmarks Argon ranks second on the main human-preference leaderboard, well above average but behind the top tier on Artificial Analysis's index, and ahead of rivals on most of Google's own tests. ### Google's Own Numbers On Google's table, Argon leads on knowledge work and long context, and splits the agentic coding tests: ahead on DeepSWE and Vibe Code Bench, behind on FrontierSWE and Terminal-Bench 4.0. The [model card](https://deepmind.google/models/model-cards/gemini-4-argon/) compares it with GPT-6 Astra, Claude Fable 5.1 and Claude Opus 5.5:
Benchmark (Google-reported)Gemini 4 ArgonBest rival
Harvey's Legal Agent Benchmark19.6%6.7% (Fable 5.1)
Vals Finance Agent v265.4%58.9% (Fable 5.1)
GraphWalks, 256k to 1M tokens84.2%71.8% (GPT-6 Astra)
DeepSWE v1.177.9%74.2% (Opus 5.5)
OSWorld-2.0 (computer use, offline subset)69.2%72.6% (GPT-6 Astra, the only rival reported)
FrontierSWE v255.0%65.5% (GPT-6 Astra)
Terminal-Bench 4.057.4%66.4% (Opus 5.5)
![Google-reported benchmark scores where Gemini 4 Argon leads and where it trails Claude Opus 5.5 and GPT-6 Astra](/blog/gemini-4-argon/gemini-4-argon-benchmarks-leads-trails.png)
Argon's score minus the best rival's on benchmarks from Google's Gemini 4 model card (vendor-reported, October 2026).
On Google's numbers, Argon is strongest on long, document-heavy knowledge work (legal, finance, very long context) and mixed on agentic coding and computer use. Its biggest gaps are FrontierSWE and Terminal-Bench Science, where it trails GPT-6 Astra by 10.5 points, and Terminal-Bench 4.0, where Opus 5.5 leads by 9. ### Independent Leaderboards On the [Arena text leaderboard](https://arena.ai/leaderboard/text) dated November 8, Argon (High) ranks second at 1522, behind Gemini 4 Carbon (High) at 1527, which is still marked preliminary. Claude Opus 5.5 is fourth at 1506. [Artificial Analysis](https://artificialanalysis.ai/leaderboards/models) puts Argon (high) at 50 on its Intelligence Index v5.0.1, below Carbon (high) at 60, Claude Opus 5.5 (max) at 59, GPT-6 Astra (max) at 57 and GPT-6.1 Sol (max) at 55. Each model is compared at its best-scoring setting. Scores from the older v4 index are not comparable, which is why you will see Argon quoted at 53 in launch-week coverage. ### Hallucination On Artificial Analysis's AA-Omniscience test, Argon (high) has the [lowest hallucination rate](https://artificialanalysis.ai/models/gemini-4-argon) of the models on its default chart. That metric counts wrong answers among all of a model's non-correct responses (wrong, partial or not attempted), so Argon rarely answers wrongly when it does not get a question right. Its accuracy on the same test is lower than Carbon's, Opus 5.5's or GPT-6.1 Sol's, so a low hallucination rate here does not mean it knows more. For how Argon stacks up against every major model by task, see our [best AI model ranking](https://geotoolbox.ai/blog/best-ai-model). For a head-to-head with Anthropic, see [Claude vs Gemini](https://geotoolbox.ai/blog/claude-vs-gemini). ## Gemini 4 Argon vs Gemini 4 Carbon: Should You Wait? Gemini 4 Carbon is Google's newer and stronger model, announced on October 28, 2026, about two weeks after Argon went public. It tops Arena and Artificial Analysis today. You almost certainly cannot use it. Google's [Carbon announcement](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/) says it is going "to a subset of cyber defenders" through the Fairwind Program first, then to more trusted partners in phases. For everyone else, Google gave no date, only that it will reach developers, businesses and consumers "as soon as possible." That is the same path Argon took, from its September 30 preview with cyber defenders to its public launch on October 13.
Gemini 4 ArgonGemini 4 Carbon
Public sinceOctober 13, 2026Not yet (Fairwind partners only)
Gemini app / AI ModeAI Pro and UltraNo
API launch price$2 / $10 per 1M, then $4 / $20Announced at the same prices, no public API yet
Arena text (Nov 8)1522, #21527, #1 (preliminary)
Artificial Analysis index v5.0.150 (high)60 (high)
For most people the answer is Argon now, because Carbon has no public plan or API date. If you are on AI Pro or Ultra, you already have Argon; Google has not said which plans Carbon will come to. If you are building on the API, Carbon was announced at the same list prices ($2/$10 introductory, then $4/$20), but Google has not dated Carbon's introductory window, and per-task cost will depend on how many tokens it spends.
![Decision flow for choosing between Gemini 4 Argon, Gemini 4 Carbon, Gemini 3.1 Pro and Gemini Flash](/blog/gemini-4-argon/which-gemini-model-decision-flow.png)
Which Gemini model to use in November 2026, by plan and job.
The one group that should not default to Argon is high-volume, cost-sensitive API users. For classification, extraction and short answers, a Flash model costs a fraction as much per token and spends fewer tokens on easy work. ## Where Argon Is Strong, and Where It Falls Short Argon earns its price on long, multi-step work where most of the effort is reading and reasoning over a lot of material. Beyond the benchmark leads above, these strengths stand out: - **Very long outputs.** By default a response stops at 65,536 tokens. With long decode and [background execution](https://aistudio.google.com/docs/latest-model), the model generates in hops of up to 64K tokens, each continuing where the last one stopped, so a single response can run to roughly 1M tokens minus your input. That suits large refactors, full reports and big code migrations. - **Agentic coding in Antigravity.** Google's [GA post](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/) describes Argon helping the Chrome team separate code out of a roughly 6-million-line legacy folder. Treat vendor case studies as a ceiling, not an average. - **Prompt injection resistance.** Google reported a 0.7% attack success rate for Argon on Gray Swan's Indirect Prompt Injection benchmark, the best result until [Carbon](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/) posted 0.0%. That matters if you let it browse or read email. The weak spots follow from the same design: - **Speed.** Artificial Analysis measured 27.7 minutes per index task, more than twice the median. - **Cost per task.** Its verbosity puts it at about $9.95 per task on Artificial Analysis's board at the December list price (roughly half at the introductory rate), and it drains the app's usage limit quickly. - **Agentic coding.** It trails on FrontierSWE and Terminal-Bench, so shell-driven agents may do better elsewhere. - **Fresh knowledge.** The March 2026 cutoff means anything newer needs search grounding. If your work is mostly short questions, you will pay for capability you do not use. ## How to Access Gemini 4 Argon There are several ways in, depending on whether you want a chat app or an API: 1. **Gemini app (web, Android, iOS, macOS):** subscribe to AI Pro or Ultra, then pick Gemini 4 Argon in the model menu. 2. **AI Mode in Google Search:** on an eligible account, select Argon from the menu in the "Ask anything" bar. See our explainer on [how Google AI Mode works](https://geotoolbox.ai/blog/what-is-google-ai-mode). 3. **Google Antigravity:** open the model picker in Google's agentic development platform with a paid AI Pro or an Ultra plan. 4. **Gemini API and Google AI Studio:** call the model ID `gemini-4-argon` on a paid API project; the [model page](https://aistudio.google.com/docs/models/gemini-4-argon) lists limits and thinking settings. 5. **Google Cloud or a router:** use Google Cloud's [Gemini Enterprise Agent Platform](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/4-argon) for enterprise controls, or third-party routers such as [OpenRouter](https://openrouter.ai/google/gemini-4-argon). ## What Argon Means for Your Brand in AI Search Argon also answers in Google Search. Since October 13, AI Pro and Ultra subscribers in supported countries can switch AI Mode answers in Google Search to Argon. Those answers are part of the same search journey your customers already use, and they cite sources. What we at geotoolbox do not know yet is whether Argon picks different sources than AI Mode's default model. We have not tested that, and Google has not said. Comparisons like [Grok vs Gemini](https://geotoolbox.ai/blog/grok-vs-gemini) show how much citation behavior differs between engines, so it is worth checking rather than assuming. The step is the same for every new model: check whether AI answers mention and cite your brand for the questions you care about, and keep checking as models change. geotoolbox's [AI Visibility Tracker](https://geotoolbox.ai/features/ai-visibility-tracker) runs your prompts through Gemini and Google AI Mode, among other engines, and records who is named and cited. Starter's fixed engines do not include those two; on Plus and Growth you can add them as part of your engine picks, and Pro and Scale run every engine. Treat any tracker's Gemini and AI Mode results, ours included, as what a default user sees: Argon only answers when a signed-in subscriber picks it. ## Frequently Asked Questions ### Is Gemini 4 Argon better than Claude Opus 5.5? It depends on the job. Argon ranks above Opus 5.5 on the [Arena text board](https://arena.ai/leaderboard/text) (1522 vs 1506 on November 8, 2026) and leads on Google's legal, finance and long-context tests, while Opus 5.5 leads on Terminal-Bench 4.0 and scores higher on the [Artificial Analysis index](https://artificialanalysis.ai/leaderboards/models) (59 at max effort vs 50 for Argon on high, each at its best setting). From December 1, 2026, both cost $4 input and $20 output per million tokens on the API, per [Google](https://aistudio.google.com/docs/pricing) and [Anthropic](https://platform.claude.com/docs/en/about-claude/pricing). ### Is Gemini 4 Argon better than ChatGPT? It depends on what you measure. Comparing Argon with GPT-6.1 Sol, the OpenAI model at Argon's price point: on the [Arena text board](https://arena.ai/leaderboard/text) Argon (1522) sits well above GPT-6.1 Sol at max effort (1482), so people prefer its answers. On the [Artificial Analysis index](https://artificialanalysis.ai/leaderboards/models), GPT-6.1 Sol at max effort scores 55 to Argon's 50 and costs $1.27 per task against $9.95. GPT-6.1 Sol's [API list price](https://developers.openai.com/api/docs/pricing) is $2 input and $10 output per million tokens for prompts up to 272K tokens, the same as Argon's introductory price through November 30, 2026. ### Can I use Gemini 4 Argon in the EU? In the Gemini app, yes: Google rolled Argon out globally on October 13, 2026 for AI Pro and Ultra subscribers. In AI Mode in Search, not yet: Google's [list of countries for Argon in AI Mode](https://support.google.com/websearch/answer/16011537) includes the UK and Switzerland but no EU member state as of November 8, 2026. ## Sources - Gemini 4 Argon: our next era of frontier intelligence (Sep 30 announcement, Fairwind preview) - Google, September 30, 2026 - `blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon` - Gemini 4 Argon: built to solve your hardest problems (GA, access by plan, introductory price footnote) - Google, October 13, 2026 - `blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon` - Gemini Developer API pricing (Gemini 4 Argon rows: Standard, Batch, Flex, Priority) - Google AI for Developers, captured November 8, 2026 - `aistudio.google.com/docs/pricing` - Gemini 4 Argon model page (model ID, token limits, thinking levels) - Google AI for Developers, captured November 8, 2026 - `aistudio.google.com/docs/models/gemini-4-argon` - Gemini 4 model card (benchmark table, knowledge cutoff) - Google DeepMind, October 13, 2026 - `deepmind.google/models/model-cards/gemini-4-argon` - Google AI plans and subscriptions (US prices, model access by plan, usage limits footnote) - Google, captured November 8, 2026 from a US connection - `gemini.google/us/subscriptions` - Get AI-powered responses with AI Mode (Gemini 4 Argon in AI Mode, eligibility, country list) - Google Search Help, captured November 8, 2026 - `support.google.com/websearch/answer/16011537` - Models in Google Antigravity (plan availability table) - Google Antigravity docs, captured November 8, 2026 - `antigravity.google/docs/models` - Gemini 4 Argon on Google Cloud Agent Platform (thinking levels) - Google Cloud, November 7, 2026 - `docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/4-argon` - Gemini 4 Carbon announcement (Fairwind access, launch price, Gray Swan result) - Google, October 28, 2026 - `blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon` - Text Arena leaderboard - Arena, November 8, 2026 - `arena.ai/leaderboard/text` - About Gemini models (thinking levels, app default) - Gemini Apps Help, captured November 8, 2026 - `support.google.com/gemini/answer/18648722` - What's new in Gemini 4 Argon (long decode, background execution, thinking levels) - Google AI for Developers, captured November 8, 2026 - `aistudio.google.com/docs/latest-model` - LLM Leaderboard (Intelligence Index v5.0.1, cost per task) - Artificial Analysis, captured November 8, 2026 - `artificialanalysis.ai/leaderboards/models` - Gemini 4 Argon model analysis and LLM leaderboard (Intelligence Index v5.0.1, AA-Omniscience, cost per task) - Artificial Analysis, captured November 8, 2026 - `artificialanalysis.ai/models/gemini-4-argon` - Claude API pricing (Opus 5.5) - Anthropic, captured November 8, 2026 - `platform.claude.com/docs/en/about-claude/pricing` - OpenAI API pricing (GPT-6.1 Sol) - OpenAI, captured November 8, 2026 - `developers.openai.com/api/docs/pricing` - Gemini 4 Argon on OpenRouter - OpenRouter, captured November 8, 2026 - `openrouter.ai/google/gemini-4-argon` - "what's wrong with Argon's usage limit?" - r/GeminiAI, October 2026 - `reddit.com/r/GeminiAI/comments/1xd6kze/whats_wrong_with_argons_usage_limit` - "Gemini 4 Argon unavailable on Jio Google AI Pro" - Google AI Developers Forum, October 2026 - `discuss.ai.google.dev/t/subject-gemini-4-argon-unavailable-on-jio-google-ai-pro/189886` - "Gemini 4 Argon unavailable for paid Google AI Pro family members" - Google AI Developers Forum, October 2026 - `discuss.ai.google.dev/t/gemini-4-argon-unavailable-for-paid-google-ai-pro-family-members-only-claude-4-6-available/189933` - "Active paid Google AI Pro shows Antigravity Starter Quota on app 2.29.0" - Google AI Developers Forum, November 2026 - `discuss.ai.google.dev/t/active-paid-google-ai-pro-shows-antigravity-starter-quota-on-app-2-29-0/198730`