# Best AI Model in November 2026: Ranked by What You Do

> The best AI model right now, ranked by job: a dated lineup, live leaderboards compared, API prices, cost per task, and the top model you cannot use yet.

- Published: 2026-11-06
- Updated: 2026-11-06
- Author: Samy BEN SADOK
- Canonical: https://geotoolbox.ai/blog/best-ai-model

---

The best AI model depends on the job, and the leaderboards no longer agree on a single winner. As of November 6, 2026, **Claude Opus 5.5** leads the coding boards, **Gemini 4 Argon** leads Arena and Mercor's agent board among models you can use, and **GPT-6.1 Sol** is the value pick for API work. **Gemini 4 Carbon** tops 3 boards but is limited to a subset of cyber defenders.

Rankings like this go stale within weeks, so every table below carries its capture date.

## The Short Answer: Best AI Model by Job

Pick by task, not by brand. These picks come from the live leaderboards and benchmark pages covered below.

<table>
<thead>
<tr><th>Job</th><th>Best pick</th><th>Runner-up</th><th>Why</th></tr>
</thead>
<tbody>
<tr><td><strong>Agentic coding</strong></td><td>Claude Opus 5.5</td><td>Claude Sonnet 5.5</td><td>First on the official Terminal-Bench 4.0 board (64.8%) and on Mercor's APEX-SWE (67.6%); Sonnet 5.5 is second on both (61.8% and 66.4%)</td></tr>
<tr><td><strong>Knowledge work and agents</strong></td><td>Claude Opus 5.5</td><td>Gemini 4 Argon</td><td>Leads Argon on Artificial Analysis (59 vs 50) and tops GDPval-AA (1866, within the margin of Kimi K3.1 Pro at 1858); Argon leads Mercor's APEX-Agents (82.4% vs 73.5%) and Arena (1520 vs 1509)</td></tr>
<tr><td><strong>Best value for API work</strong></td><td>GPT-6.1 Sol</td><td>GPT-6 Astra (high effort)</td><td>Scores 55 on Artificial Analysis at $1.27 per task, against $10.04 for Opus 5.5 at 59; ties Astra (max) at 58.2% on Terminal-Bench 4.0 for a fraction of the run cost</td></tr>
<tr><td><strong>Low-cost, high-volume API work</strong></td><td>GPT-6.1 Sol (medium effort)</td><td>GPT-6.1 Terra (xhigh effort)</td><td>Scores 46 at $0.36 per task, the score Kimi K3.1 Pro reaches at $3.68; Terra at xhigh effort scores 45 at $0.40</td></tr>
<tr><td><strong>Top score, not available</strong></td><td>Gemini 4 Carbon</td><td>none</td><td>#1 on Arena, Artificial Analysis and Mercor's agent board, but not publicly available</td></tr>
<tr><td><strong>Self-hosting</strong></td><td>Kimi K3.1 Pro</td><td>DeepSeek V4.1 Flash</td><td>Top open model on Artificial Analysis at 46, about 14 points behind the leaders</td></tr>
</tbody>
</table>

If you only want one name for code and knowledge-work tasks, use Opus 5.5. If you want the best Arena and agent scores you can buy today, look at Gemini 4 Argon. Free tiers and plan prices are in the plan table further down.

## The Current Lineup, Captured November 6, 2026

Right now, 9 closed models and 1 open-weight leader matter among the top AI models. Prices are USD per million tokens (input / output) at standard rates; the full rate card sits in our [AI token cost guide](https://geotoolbox.ai/blog/ai-token-cost).

<table>
<thead>
<tr><th>Model</th><th>Maker</th><th>API price (in / out)</th><th>Context window</th><th>Where you can use it</th></tr>
</thead>
<tbody>
<tr><td><strong><a href="https://www.anthropic.com/news/claude-opus-5-5">Claude Opus 5.5</a></strong></td><td>Anthropic</td><td>$4 / $20</td><td>1M</td><td>Claude Pro ($20) and above, API</td></tr>
<tr><td><strong><a href="https://geotoolbox.ai/blog/claude-fable-5-1">Claude Fable 5.1</a></strong></td><td>Anthropic</td><td>$10 / $50</td><td>1M</td><td>Claude Max ($100) and Ultra ($200); Pro only through usage credits; API</td></tr>
<tr><td><strong>Claude Sonnet 5.5</strong></td><td>Anthropic</td><td>$2 / $10</td><td>1M</td><td>Claude plans, API</td></tr>
<tr><td><strong><a href="https://developers.openai.com/api/docs/models/gpt-6-astra">GPT-6 Astra</a></strong></td><td>OpenAI</td><td>$10 / $50</td><td>1.05M</td><td>ChatGPT Pro as GPT-6 Pro; Plus only inside Work and Codex; API</td></tr>
<tr><td><strong>GPT-6.1 Sol</strong></td><td>OpenAI</td><td>$2 / $10</td><td>1.05M (500K default in Work and Codex)</td><td>API; ChatGPT Work and Codex</td></tr>
<tr><td><strong>Gemini 4 Argon</strong></td><td>Google</td><td>$2 / $10 through November 30, then $4 / $20</td><td>1M</td><td>Gemini app and AI Mode for Google AI Pro ($19.99) and Ultra; API</td></tr>
<tr><td><strong><a href="https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/">Gemini 4 Carbon</a></strong></td><td>Google</td><td>Not on sale (announced launch price: $2 / $10 at first, then $4 / $20)</td><td>1M</td><td>A subset of cyber defenders through Google's Fairwind Program</td></tr>
<tr><td><strong><a href="https://about.fb.com/news/2026/10/introducing-muse-wonder-models/">Muse Wonder</a></strong></td><td>Meta</td><td>$4 / $20 as listed by Arena</td><td>1M</td><td>Meta Model API and Muse Code</td></tr>
<tr><td><strong><a href="https://x.ai/news/grok-4-7">Grok 4.7</a></strong></td><td>xAI</td><td>$2 / $6</td><td>500K</td><td>API, Cursor and Grok Build</td></tr>
<tr><td><strong><a href="https://huggingface.co/moonshotai/Kimi-K3.1-Pro">Kimi K3.1 Pro</a></strong></td><td>Moonshot AI</td><td>Open weights</td><td>1M</td><td>Hugging Face download under a custom license; hosted APIs</td></tr>
</tbody>
</table>

<p><em>Captured November 6, 2026 from each vendor's pages. Plan prices are the standard US monthly rates.</em></p>

A couple of rows deserve a second look. Opus 5.5 costs **$4 / $20**, down from $5 / $25 for Opus 5. The Argon rate is an introductory price, covered under [What Changes Next](#what-changes-next). Long prompts cost more than the table shows: OpenAI bills GPT-6 Astra at 2x input and 1.5x output for the whole request once a prompt passes 272K input tokens, and xAI charges different rates for Grok 4.7 requests that exceed 200K tokens.

GPT-6 Sol and GPT-6.1 Sol are separate models. OpenAI's help article describes standard ChatGPT Chat as running GPT-6 Sol, and lists GPT-6.1 Sol as its own model option for ChatGPT Work and Codex.

### Gemini 4 Carbon: The Top Score You Cannot Buy

Carbon leads 3 leaderboards, and Google's own AI Overview for "best AI model" lists it among the current leaders with no access caveat. Google's [launch post](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/) says it will make Carbon "available to a subset of cyber defenders" and phase in more trusted partners through the Fairwind Program. Google says it wants to open Carbon to developers, businesses and consumers "as soon as possible", and gives no date. Today there is no public plan and no general API.

For a buyer, Carbon is not an option yet. Treat its scores as a preview of where Gemini is heading, and pick from the models you can sign up for.

## Why the Leaderboards Disagree

Every LLM ranking measures something different, so the order changes from board to board. The 4 boards below name 2 different winners: Carbon leads Arena, Artificial Analysis and Mercor's agent board, and Opus 5.5 leads Terminal-Bench. Among models you can use, Argon leads 2 boards and Opus 5.5 leads 2.

<table>
<thead>
<tr><th>Board</th><th>What it measures</th><th>#1</th><th>#2</th><th>#3</th><th>Date</th></tr>
</thead>
<tbody>
<tr><td><strong><a href="https://arena.ai/leaderboard/text">Arena, Text overall</a></strong></td><td>Blind human votes, 418 models</td><td>Gemini 4 Carbon (High) 1528, preliminary</td><td>Gemini 4 Argon (High) 1520</td><td>Claude Opus 5.5 (High) 1509</td><td>Board dated October 27, 2026</td></tr>
<tr><td><strong><a href="https://artificialanalysis.ai/leaderboards/models">Artificial Analysis Intelligence Index</a></strong></td><td>Its own evals, run independently</td><td>Gemini 4 Carbon (high) 60</td><td>Claude Opus 5.5 (max) 59</td><td>GPT-6 Astra (max) 57</td><td>Captured November 6, 2026</td></tr>
<tr><td><strong><a href="https://www.mercor.com/apex/apex-agents-leaderboard/">Mercor APEX-Agents</a></strong></td><td>Expert-written professional tasks</td><td>84.2% (Gemini 4 Carbon)</td><td>82.4% (Gemini 4 Argon)</td><td>77.6% (Tencent Hy4)</td><td>Live board, captured November 6, 2026</td></tr>
<tr><td><strong><a href="https://www.tbench.ai/leaderboard">Terminal-Bench 4.0, official</a></strong></td><td>Command-line agent tasks</td><td>64.8% (Claude Opus 5.5)</td><td>61.8% (Claude Sonnet 5.5)</td><td>58.2% (GPT-6 Astra and GPT-6.1 Sol)</td><td>Captured November 6, 2026</td></tr>
</tbody>
</table>

<p><em>Captured November 6, 2026. Scores are not comparable across boards. Artificial Analysis lists several effort settings per model; this table shows the best setting for each model.</em></p>

<figure className="not-prose my-8">
  ![Top rows of the Artificial Analysis LLM leaderboard on November 6, 2026: Gemini 4 Carbon (high) 60, Claude Opus 5.5 (max) 59, Gemini 4 Carbon (medium) 58, Claude Opus 5.5 (xhigh) 57, GPT-6 Astra (max) 57, with cost per task, time per task and latency for each](/blog/best-ai-model/artificial-analysis-leaderboard-top-rows.png)
  <figcaption className="mt-3 text-center text-sm text-gray-500">Artificial Analysis leaderboard, top rows, captured November 6, 2026. Each model appears once per effort setting.</figcaption>
</figure>

Opus 5.5 is fifth on the Mercor agent board at 73.5%, behind Carbon (84.2%), Argon (82.4%), Tencent Hy4 (77.6%) and Sonnet 5.5 (75.5%). Meta's Muse Wonder (Max) is fourth on Arena at 1507.

### Preference, Independent Index, Agent Boards

Each board answers a different question, which is why the order changes.

Arena ranks models by blind human preference. It rewards answers people like, not answers that are correct. Carbon's 1528 is flagged preliminary and rests on 4,403 votes, against 11,889 for Argon and 11,415 for Opus 5.5.

Artificial Analysis runs every model itself, and the effort setting changes the result a lot. Opus 5.5 scores 59 at max effort and 52 at high. When Google launched Carbon it cited 59 on the index; the live page now shows 60, so even one board moves.

Mercor and Terminal-Bench test agents, so each score covers the model plus its tooling. Terminal-Bench lists the agent beside every result: Claude Code for the Claude models and Codex for the OpenAI models. Mercor's live board is newer than its own September 23 "best models" page, which predates the Argon and Carbon launches and still puts Opus 5.5 first.

Vendor tables are self-run. Anthropic's own [Opus 5.5 post](https://www.anthropic.com/news/claude-opus-5-5) warns that "benchmark margins have become a less reliable guide to real-world differences", and its Terminal-Bench 4.0 row compares Opus 5.5 at xhigh effort with GPT-6 Astra at high effort, as reported by OpenAI. Anthropic says each figure is that model's highest score, but the settings differ.

Benchmarks also expire. OpenAI [stopped reporting SWE-bench Verified](https://openai.com/index/why-we-no-longer-evaluate-swe-bench-verified/) because of flawed tests and contamination, and now recommends SWE-bench Pro. A coding score from an older leaderboard may measure a test at least one lab has stopped reporting.

### What We Tested, and What We Only Cite

Every benchmark score on this page is cited from its owner with a date. We did not rerun any of them. The one dataset we produced ourselves at geotoolbox is a panel: on November 6, 2026 we put 8 model-choice questions to 5 AI engines and logged every source each one cited. The 5 were a logged-out ChatGPT scrape plus an API call, Gemini, Google AI Mode, Perplexity's Sonar API and a Claude agent with web search.

The engines cited 183 distinct domains. Of those, 152 appeared in only one engine, and only 15 were cited by 3 or more, almost all vendor documentation plus leaderboards: anthropic.com, openai.com, x.ai, Artificial Analysis, Arena, BenchLM and LLM Stats. Outside that shared core, the engines mostly disagree on what to cite.

## Best AI Model for Coding

For agentic coding, **Claude Opus 5.5** is the best LLM on the evidence that does not come from a vendor's own launch post, with Claude Sonnet 5.5 second and GPT-6.1 Sol the one to pick when cost matters.

On the official Terminal-Bench 4.0 board, Opus 5.5 scores 64.8% with Claude Code and Sonnet 5.5 61.8%. GPT-6 Astra and GPT-6.1 Sol tie at 58.2% with Codex, and Fable 5.1 follows at 57.9%. The board also lists what each run cost, and GPT-6.1 Sol's was a fraction of Opus 5.5's and Sonnet 5.5's.

Mercor's live [APEX-SWE board](https://www.mercor.com/apex/apex-swe-leaderboard/) agrees on the top 2: Opus 5.5 at 67.6% and Sonnet 5.5 at 66.4%, then Opus 5 at 63.7% and Fable 5.1 at 63.6% among the entries its chart shows. Mercor reports each model with the harness that scores it highest, here Terminus-2.

Open weights are close on this one benchmark. [Moonshot's model card](https://huggingface.co/moonshotai/Kimi-K3.1-Pro) reports 65.7% for Kimi K3.1 Pro on Terminal-Bench 4.0 using the Claude Code harness, and its table takes other models' scores from their blog posts or the official leaderboard, so it is a vendor figure like any other.

The coding tool wraps the model and changes the score, so it matters too. For deeper dives, see our [Kimi K3 vs Claude comparison](https://geotoolbox.ai/blog/kimi-k3-vs-claude), the [GPT-6 Astra breakdown](https://geotoolbox.ai/blog/gpt-6-astra) and the [Claude Fable 5.1 review](https://geotoolbox.ai/blog/claude-fable-5-1).

## Best AI Model for Writing, Research, and Long Documents

For knowledge work the boards split. Opus 5.5 tops [Artificial Analysis's GDPval-AA](https://artificialanalysis.ai/evaluations/gdpval-aa) at 1866, within the margin of Kimi K3.1 Pro (1858) and Muse Wonder Full (1857); Gemini 4 Argon sits far down that board at 1631. Argon leads Mercor's professional-tasks board (82.4% to 73.5% for Opus 5.5) and sits above Opus on Arena. Test both on your own documents.

Context size is the one hard number here, and the top models are close. Claude Opus 5.5, Fable 5.1 and Sonnet 5.5 all take 1M tokens. [GPT-6 Astra](https://developers.openai.com/api/docs/models/gpt-6-astra) has a 1,050,000-token window, of which up to 922,000 can be input and 128,000 output. Gemini 4 Argon offers a 1M unified input-output limit through the API, and Grok 4.7 stops at 500K.

Writing quality has no neutral score beyond preference votes, and Arena's votes put Gemini and Claude models on top. For research, the major apps each ship a research mode (ChatGPT's [plans page](https://chatgpt.com/pricing) lists deep research on every plan, for example). We found no independent head-to-head test of them, so we do not rank them. For broader comparisons of the apps themselves, see [Claude vs ChatGPT](https://geotoolbox.ai/blog/claude-vs-chatgpt), [Claude vs Gemini](https://geotoolbox.ai/blog/claude-vs-gemini) and [Gemini vs ChatGPT](https://geotoolbox.ai/blog/gemini-vs-chatgpt).

## Best Value: Cost per Task, Not Price per Token

List prices mislead because models spend different amounts of reasoning on the same job. [Artificial Analysis](https://artificialanalysis.ai/leaderboards/models) publishes a cost-per-task column next to each score, and it shows the real gap.

<table>
<thead>
<tr><th>Model (effort)</th><th>Index score</th><th>Cost per task</th><th>List price (in / out)</th></tr>
</thead>
<tbody>
<tr><td>Claude Opus 5.5 (max)</td><td>59</td><td>$10.04</td><td>$4 / $20</td></tr>
<tr><td>Claude Opus 5.5 (xhigh)</td><td>57</td><td>$6.05</td><td>$4 / $20</td></tr>
<tr><td>GPT-6 Astra (max)</td><td>57</td><td>$6.24</td><td>$10 / $50</td></tr>
<tr><td>GPT-6 Astra (high)</td><td>55</td><td>$3.24</td><td>$10 / $50</td></tr>
<tr><td>Claude Sonnet 5.5 (max)</td><td>55</td><td>$10.02</td><td>$2 / $10</td></tr>
<tr><td><strong>GPT-6.1 Sol (max)</strong></td><td>55</td><td>$1.27</td><td>$2 / $10</td></tr>
<tr><td>GPT-6.1 Sol (xhigh)</td><td>52</td><td>$0.76</td><td>$2 / $10</td></tr>
<tr><td>GPT-6.1 Sol (medium)</td><td>46</td><td>$0.36</td><td>$2 / $10</td></tr>
<tr><td>Kimi K3.1 Pro</td><td>46</td><td>$3.68</td><td>Open weights</td></tr>
<tr><td>Grok 4.7 (xhigh)</td><td>35</td><td>$7.77</td><td>$2 / $6</td></tr>
</tbody>
</table>

<p><em>Artificial Analysis, captured November 6, 2026. Cost per task is the column the site reports for its own task set.</em></p>

<figure className="not-prose my-8">
  ![Bar chart of Artificial Analysis cost per task on November 6, 2026: GPT-6.1 Sol at max effort $1.27, GPT-6 Astra at high effort $3.24, Kimi K3.1 Pro $3.68, Claude Opus 5.5 at xhigh effort $6.05, Claude Sonnet 5.5 at max effort $10.02, Claude Opus 5.5 at max effort $10.04](/blog/best-ai-model/ai-model-cost-per-task-chart.png)
  <figcaption className="mt-3 text-center text-sm text-gray-500">GPT-6.1 Sol and Claude Sonnet 5.5 share a $2 / $10 list price and a score of 55, but Sonnet costs $10.02 per task against $1.27 for Sol.</figcaption>
</figure>

Read it 4 ways. GPT-6.1 Sol and Claude Sonnet 5.5 both list at $2 / $10 and both score 55 at max effort, yet GPT-6.1 Sol costs $1.27 per task and Sonnet $10.02. Matching 55 with GPT-6 Astra costs $3.24 at high effort. And Opus 5.5 buys its last 2 points (57 to 59) for about $4 more per task. At the low end, GPT-6.1 Sol at medium effort scores 46 for $0.36 per task, the score Kimi K3.1 Pro reaches for $3.68.

Effort is the lever. Opus 5.5 runs from 35 at low effort to 59 at max on the same page, so a leaderboard score without an effort setting tells you little. The rest of the rate card, including cached input and batch discounts, is in the guide linked above. Speed matters too: GPT-6.1 Sol at max effort takes about 22 minutes per task on the same page, against about 9 for Astra at high effort and about 28 for Opus 5.5 at max.

## Best Open-Weight Models

The open-weight leader is **Kimi K3.1 Pro**. Artificial Analysis lists it as the highest-ranked of the 39 open-weights models on its 98-model board, at 46. That is about 14 points behind Carbon (60) and 13 behind Opus 5.5 (59). The [model card](https://huggingface.co/moonshotai/Kimi-K3.1-Pro) lists 2.8T total parameters with 104B active, under a custom Kimi K3.1 Pro License.

Behind it, [Artificial Analysis](https://artificialanalysis.ai/models/open-source) shows DeepSeek V4.1 Flash 1017 (max) at 33 and GLM-5.3 (max) at 32, a wide drop from Kimi. "Open weights" is not "open source": read each license before you build a product on a model. Our guides to the [best open-source LLMs](https://geotoolbox.ai/blog/best-open-source-llms) and to [Chinese AI models compared](https://geotoolbox.ai/blog/chinese-ai-models-compared) cover licenses and hosting in more detail, and our guide to [running an LLM locally](https://geotoolbox.ai/blog/run-llm-locally) covers the hardware side.

## What Your Paid Plan Actually Buys

A model on a leaderboard and the model in your app are not the same thing. The same vendor can serve one model through the API, another in Chat, and a third inside its coding tool.

<table>
<thead>
<tr><th>Plan</th><th>Monthly price</th><th>What runs</th></tr>
</thead>
<tbody>
<tr><td><strong>ChatGPT Free</strong></td><td>$0</td><td>Unlimited text chats with GPT-6 on OpenAI's plans page; OpenAI's help article still lists GPT-5.6 Luna as the Free default</td></tr>
<tr><td><strong>ChatGPT Go</strong></td><td>$8</td><td>More messages, uploads and image creation than Free</td></tr>
<tr><td><strong>ChatGPT Plus</strong></td><td>$20</td><td>GPT-6 Sol in standard Chat (rolling out); GPT-6 Astra only inside Work and Codex</td></tr>
<tr><td><strong>ChatGPT Pro</strong></td><td>From $100 a month, with 3 usage tiers (Pro 100, Pro 200 and Pro 500)</td><td>GPT-6 Pro, powered by GPT-6 Astra, in Chat on Pro 100 and Pro 200; OpenAI's help article does not name Pro 500</td></tr>
<tr><td><strong><a href="https://claude.com/pricing">Claude Pro</a></strong></td><td>$20 ($17 billed annually)</td><td>Opus, Sonnet and Haiku; Fable only through usage credits</td></tr>
<tr><td><strong>Claude Max and Ultra</strong></td><td>$100 and $200</td><td>Fable included, up to half your weekly limit, on top of everything in Pro</td></tr>
<tr><td><strong>Gemini free tier</strong></td><td>$0</td><td>The Flash-Lite model</td></tr>
<tr><td><strong><a href="https://gemini.google/us/subscriptions/">Google AI Plus</a></strong></td><td>$4.99</td><td>The Flash model; Gemini 4 Argon starts at AI Pro</td></tr>
<tr><td><strong>Google AI Pro</strong></td><td>$19.99</td><td>Gemini 4 Argon, Pro and Flash models in the Gemini app and AI Mode</td></tr>
<tr><td><strong><a href="https://x.ai/news/x-subscription">X Subscription Premium</a></strong></td><td>$30</td><td>Grok, Cursor Pro and X Premium+ benefits, with 4x the usage of the Plus tier</td></tr>
</tbody>
</table>

<p><em>Standard US monthly prices, captured November 6, 2026. See <a href="https://geotoolbox.ai/blog/chatgpt-pricing">ChatGPT pricing</a>, <a href="https://geotoolbox.ai/blog/claude-pricing">Claude pricing</a>, <a href="https://geotoolbox.ai/blog/gemini-pricing">Gemini pricing</a> and <a href="https://geotoolbox.ai/blog/grok-pricing">Grok pricing</a> for the full plan lists.</em></p>

<figure className="not-prose my-8">
  ![Diagram of three layers people mix up when choosing an AI model: the model, your subscription plan, and the app mode such as Chat versus Work and Codex](/blog/best-ai-model/ai-model-vs-plan-vs-app-diagram.png)
  <figcaption className="mt-3 text-center text-sm text-gray-500">Same vendor, several layers: the model you read about, the plan you pay for, and the mode of the app you open.</figcaption>
</figure>

OpenAI's [help article on GPT-6 in ChatGPT](https://help.openai.com/en/articles/20001354-gpt-6-and-other-models-in-chatgpt) says GPT-6 Pro is available on the $100 and $200 Pro plans, and that Plus includes Astra in Work and Codex. So the roughly $20 plan buys a different tier of model at each vendor: Opus at Claude Pro, Argon at Google AI Pro and GPT-6 Sol (rolling out) at ChatGPT Plus, with GPT-6 Pro in Chat reserved for Pro. If you only chat, the free tiers are the place to start.

Looking for ChatGPT alternatives by job? Start with our guide to the [best ChatGPT alternatives](https://geotoolbox.ai/blog/chatgpt-alternatives).

## How to Choose for Your Own Work

A leaderboard shortlists models. Your own tasks decide.

1. Check each vendor's data terms first if you handle client or customer data.
2. Shortlist 3 models that rank in the top 5 on at least 2 boards for your kind of work.
3. Match the settings. Compare scores at the same effort level and with the same tool, because both move results.
4. Run 20 to 50 of your own tasks through the tool you will use: the API, Claude Code, Codex, or the chat app.
5. Score whether the answer is correct, what the run cost, and how long it took.
6. Re-test when a vendor ships. Google released Carbon about 2 weeks after Argon, so a shortlist can be out of date within a month.

For a primer on why models behave differently on the same prompt, see [how AI models think](https://geotoolbox.ai/blog/how-ai-models-think).

## What Changes Next

Watch these on this page.

- Argon's price: Google's [launch post](https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/) sets $2 / $10 as an introductory rate that ends November 30, 2026. After that, $4 / $20 applies.
- Carbon's rollout: Google plans to move Carbon beyond cyber defenders "as soon as possible". When it does, the answer to "best AI model" probably changes.
- The boards: Arena's board is dated October 27 and Artificial Analysis, Mercor and Terminal-Bench refresh as models and effort settings are added.

We recheck this page by November 20, 2026.

## Check How Each AI Engine Answers About Your Brand

Your customers ask these same models for recommendations. On our model-choice questions, the 5 engines rarely cited the same sources, so a brand that shows up in one engine's answer can be absent from another's.

The geotoolbox [AI visibility tracker](https://geotoolbox.ai/features/ai-visibility-tracker) runs your own prompts through the engines your plan covers, then lists which sources each one cited and whether your brand is mentioned. To see what your robots.txt allows AI crawlers to read, start with the free [AI readiness check](https://geotoolbox.ai/tools/ai-readiness).

## Frequently Asked Questions

### Which is the best AI model right now?

It depends on the job. Claude Opus 5.5 is the pick for coding, Gemini 4 Argon for Arena and agent scores among models you can use, and GPT-6.1 Sol for value per task. Gemini 4 Carbon scores higher on 3 boards but is not available yet.

### Is Gemini 4 Carbon available to the public?

No. Google says Carbon is available to a subset of cyber defenders and will phase in more trusted partners through its Fairwind Program. It has not published a date for wider access, although Arena and Artificial Analysis already list it.

### What are the major AI model families?

The major families are OpenAI's GPT, Anthropic's Claude, Google's Gemini and xAI's Grok. Meta's Muse Wonder and open-weight models such as Kimi K3.1 Pro are the main alternatives.

### What is better than ChatGPT?

On Arena, Gemini 4 Argon and Claude Opus 5.5 outrank every OpenAI model, and Opus 5.5 does too on Artificial Analysis (59 against 57 for GPT-6 Astra). For price per task, GPT-6.1 Sol is the cheapest model scoring 55 in the value table.

## Sources

- Introducing Claude Opus 5.5 ($4/$20 per MTok, launch benchmark table) - Anthropic, September 22, 2026 - `anthropic.com/news/claude-opus-5-5`
- Gemini 4 Carbon: our next frontier model (Fairwind access, announced launch price) - Google, October 28, 2026 - `blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon`
- Gemini 4 Argon launch post (introductory pricing through November 30, 2026) - Google, captured November 6, 2026 - `blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon`
- LLM Leaderboard, Intelligence Index and cost per task - Artificial Analysis, captured November 6, 2026 - `artificialanalysis.ai/leaderboards/models`
- GDPval-AA evaluation - Artificial Analysis, captured November 6, 2026 - `artificialanalysis.ai/evaluations/gdpval-aa`
- Open source model leaderboard - Artificial Analysis, captured November 6, 2026 - `artificialanalysis.ai/models/open-source`
- Text Arena overall leaderboard - Arena, board dated October 27, 2026 - `arena.ai/leaderboard/text`
- APEX-Agents leaderboard - Mercor, captured November 6, 2026 - `mercor.com/apex/apex-agents-leaderboard`
- APEX-SWE leaderboard - Mercor, captured November 6, 2026 - `mercor.com/apex/apex-swe-leaderboard`
- Terminal-Bench 4.0 leaderboard - Terminal-Bench, captured November 6, 2026 - `tbench.ai/leaderboard`
- GPT-6 Astra model page (context, pricing, long-prompt rates) - OpenAI developer docs, captured November 6, 2026 - `developers.openai.com/api/docs/models/gpt-6-astra`
- GPT-6 and other models in ChatGPT - OpenAI Help Center, captured November 6, 2026 - `help.openai.com/en/articles/20001354-gpt-6-and-other-models-in-chatgpt`
- ChatGPT plans (US prices, deep research on every plan) - OpenAI, captured November 6, 2026 - `chatgpt.com/pricing`
- Why we no longer evaluate SWE-bench Verified - OpenAI, captured November 6, 2026 - `openai.com/index/why-we-no-longer-evaluate-swe-bench-verified`
- Grok 4.7 announcement (pricing, availability) - xAI, September 21, 2026 - `x.ai/news/grok-4-7`
- The X Subscription (plan prices) - xAI, October 12, 2026 - `x.ai/news/x-subscription`
- Claude plans and pricing - Anthropic, captured November 6, 2026 - `claude.com/pricing`
- Introducing Muse Wonder and Muse Wonder Full - Meta, October 12, 2026 - `about.fb.com/news/2026/10/introducing-muse-wonder-models`
- Kimi K3.1 Pro model card - Moonshot AI, Hugging Face, captured November 6, 2026 - `huggingface.co/moonshotai/Kimi-K3.1-Pro`
- Google AI plans and pricing (US) - Google, captured November 6, 2026 - `gemini.google/us/subscriptions`
- Grok 4.7 model page (500K context, higher rates above 200K) - xAI docs, captured November 6, 2026 - `docs.x.ai/developers/models/grok-4.7`
- GPT-6.1 Sol model page (context window) - OpenAI developer docs, captured November 6, 2026 - `developers.openai.com/api/docs/models/gpt-6.1-sol`
- Models overview and pricing (Claude context windows, Sonnet 5.5 price) - Anthropic docs, captured November 6, 2026 - `platform.claude.com/docs/en/about-claude/pricing`
- Best AI models right now (older order, September 23, 2026) - Mercor - `mercor.com/resources/apex/best-ai-models-llms`