Claude Mythos (Capybara): Anthropic's Secret Model That Promises to Change Everything

In March 2026, Fortune published a report that shook the artificial intelligence market. The article revealed details about a new Anthropic model with an internal codenameCapybara, classified by the company itself as a "step change" in capacity. The model, which is being externally calledClaude Mythos, represents something the industry hasn't seen since the jump from GPT-3 to GPT-4: a qualitative change, not just an incremental one.

This article brings together everything that is known until April 2026 about Mythos, from the data from the Fortune leak to the practical implications for those who work with AI every day. If you are a developer, marketer or use Claude Code as a work tool, what lies ahead could radically change the way you operate.

1. What is Claude Mythos (codename Capybara)

The Claude Mythos is Anthropic's next full-size model, positioned as an entirely new tier above the Opus family. While Anthropic until now worked with three model levels -- Haiku (fast and cheap), Sonnet (balanced) and Opus (maximum performance) --, Mythos opens a fourth category that the company internally describes as "frontier-plus".

The codename Capybara follows Anthropic's tradition of using animal names for its models during development. Haiku, Sonnet and Opus are the public names of the Claude family, but internally each version has a zoological codename. Capybara is the first whose codename was leaked before the public release.

What we know for sure

• It exists and is being tested:the model is not speculation. Fortune confirmed with internal Anthropic sources that it is in the evaluation phase with selected clients
• And superior to Opus 4.6:internal benchmarks show scores consistently above Opus 4.6 in all categories tested
• There is no public release date:Anthropic has not confirmed when (or if) the model will be made available to the general public
• "Step change" is the official term:Anthropic itself uses this term to describe the magnitude of the improvement, differentiating it from incremental updates such as the transition from Opus 4.5 to 4.6

What is still speculation

• The final public name (Mythos is the term most used by the community, but has not been confirmed by Anthropic)
• The price and access model
• If there will be a context window larger than 1M tokens
• Whether it will be integrated into Claude Code from launch

2. The Fortune leak: what we know

The Fortune report, published in March 2026, was based on interviews with internal Anthropic sources and costmers participating in the early-access program. The key points of the report:

First, Anthropic has been working on Capybara for at least 8 months, with a dedicated team setote from the teams maintaining the Opus, Sonnet and Haiku versions. This suggests that this is not a fine-tuning of Opus, but an architecture that incorporates significant advances in training.

Second, testing with early-access costmers began in early 2026. These costmers include large technology companies and research organizations. Feedback, according to sources, was described as "unanimously positive", with several costmers reporting that the model resolved problems that were considered beyond the scope of Opus 4.6.

Third, Anthropic would be evaluating different launch strategies. One possibility is to create a setote premium tier, above the current Max plan. Another is to integrate Mythos into the existing Max plan, gradually replacing Opus as the reference model.

3. A tier above Opus: what that means

To understand the impact of Mythos, you need to understand where Opus 4.6 already is. The Claude Opus 4.6, launched in early 2026, is currently one of the most capable models on the market. It offers a 1 million token context window, native support for Agent Teams (multiple coordinated sub-agents) and agent hooks for advanced automation.

When Anthropic says that Mythos is a "step up from Opus," it is making an extraordinary statement. Opus 4.6 is already considered state of the art in several tasks. A qualitative leap above it implies capabilities that, today, seem theoretical.

What "step change" means in practice

The difference between incremental improvement and step change is like the difference between a car that goes from 200 to 220 km/h and a car that starts to fly. Incremental improvements are more speed, fewer errors, better responses. One step change is to solve entire classes of problems that were previously impossible.

Concrete examples of what a step change could mean:

• Deep multi-step reasoning:solve problems that require 50+ logical steps linked together without losing coherence
• Analysis of complex systems:understand and debug million-line codebases as a whole, not just file by file
• Long strategic planning:generate detailed project plans with dozens of dependencies and critical paths
• Expanded autonomy:perform complex tasks with less human supervision, making intermediate decisions reliably

4. Benchmarks scores: coding, reasoning and cybersecurity

The most concrete data from the Fortune leak are the benchmarks. According to sources, Capybara presented higher scores than Opus 4.6 in three main categories:

Coding

Opus 4.6 was already a reference in code generation and analysis, surpassing GPT-5.4 in benchmarks such as SWE-bench and HumanEval. Capybara, according to leaked data, significantly expands this advantage. The sources specifically mention improvements in:

• Legacy code debugging:ability to understand and fix bugs in old projects with scant documentation
• Refactoring at scale:restructure entire codebases while maintaining compatibility and without introducing regressions
• Test generation:create comprehensive test suites that cover edge cases that Opus 4.6 did not identify
• Reasoning about architecture:understand architectural trade-offs and suggest structural changes with technical justification

Reasoning

The reasoning category is where the “step change” seems most pronounced. While Opus 4.6 already outperformed competing models in logical and mathematical reasoning tasks, Capybara would have demonstrated the ability to solve problems that require much longer and more complex chains of thought. The sources speak of "deep multi-hop reasoning", where the model manages to maintain coherence over dozens of linked logical steps.

This has direct implications for tasks such as complex financial analysis, scientific research, project planning and any scenario where thinking needs to be systematic and deep.

Cybersecurity

The mention of cybersecurity in the leak is particularly interesting. According to sources, Capybara has demonstrated superior capabilities in:

• Vulnerability analysis:identify security flaws in code that other models (and many humans) would not detect
• Attack simulation:understand and describe complex attack vectors for defensive security testing purposes
• Automated security audit:analyze entire systems and produce detailed risk reports

Anthropic has historically invested heavily in AI safety (and is one of the founding companies behind the concept of "AI safety"). That Capybara stands out in cybersecurity makes sense within the company's strategy of positioning its models as the most reliable on the market.

5. Early-access testing: who is already using it

Anthropic has an early-access program for enterprise costmers who pay significant annual contracts. These clients typically include Fortune 500 technology companies, research labs and government organizations.

According to the leak, Capybara's early-access costmers were selected based on two criteria: volume of use of Opus 4.6 and complexity of use cases. Anthropic wanted to test the model in real-world scenarios that stress its new capabilities, not just synthetic benchmarks.

Feedback from early-testers, as reported by Fortune, includes:

• A fintech company that reported that Capybara solved a financial reconciliation problem that its team had been trying to automate for 6 months with Opus 4.6 without success
• A research lab that used the model to analyze experimental data and identify patterns that were not visible with previous tools
• A security company that tested the model in a code audit and found vulnerabilities that specialized SAST/DAST tools had not detected

These reports are anecdotal and not independently verified, but are consistent with the description of "step change" that Anthropic uses internally.

6. Anthropic Timeline: from Haiku to Capybara

To understand where the Mythos fits in, it’s worth revisiting the evolution of Anthropic’s models:

Period	Model	Main milestone
2024 Q1	Claude 3 (Haiku, Sonnet, Opus)	First family of three tiers
2024 Q3	Claude 3.5 Sonnet	Sonnet surpasses the original Opus in several tasks
2025 Q1	Claude 3.5 Haiku + Sonnet updated	Haiku is as good as the original Opus
2025 Q2	Claude 4 Opus (Opus 4.5)	200K window, leap in coding and reasoning
2025 Q3	Claude Sonnet 4, Claude Code 1.0	Claude Code launched as official product
2025 Q4	Claude Opus 4.5 updated	Incremental improvements, agent capabilities
2026 Q1	Claude Opus 4.6	1M tokens, Agent Teams, agent hooks
2026 Q1	Claude Haiku 4, Sonnet 4 updated	The whole family updated
2026 Q2-Q3?	Claude Mythos (Capybara)	New tier above Opus -- "step change"

The pattern is clear: Anthropic accelerates the pace of launches and each new model not only improves, but redefines what was possible. The Mythos is the next step on that path, and if the description of "step change" is accurate, it could be the biggest leap forward since the original Claude 3.

Launch estimate

Anthropic has not confirmed any dates. Based on the early-access testing stage reported in March 2026, and considering that Opus 4.6 took around 3 months between early-access and public release, the most conservative estimate points toQ3 2026 (July-September). A more cautious estimate places the launch atQ4 2026 (October-December), considering that a model of this magnitude may require more time for safety assessment.

7. Comparison with the current Opus 4.6

To put Mythos into perspective, here's what Opus 4.6 already offers and what Mythos promises to surpass:

Capacity	Opus 4.6 (current)	Mythos (estimated)
Context window	1M tokens	1M+ (possibly larger)
Coding (SWE-bench)	Best in category	Superior scores confirmed
Logical reasoning	Excellent	"Step change" -- deep multi-hop
Cybersecurity	Bom	Superior scores confirmed
Agent Teams	Yes (coordinated sub-agents)	Probably yes + improvements
Agent hooks	Sim	Probably yes + improvements
Speed	Slower than Sonnet	Unknown
Cost	Premium (Max plan)	Probably new premium tier
Availability	Public	Early-access only (Apr 2026)

The critical point is that Opus 4.6 is already extraordinarily capable. A model that measurably surpasses it in coding, reasoning and security opens up possibilities that are currently limited not by the tool, but by the model's capacity. Think about tasks you abandon because Claude "can't do it" -- Mythos could be the model that finally solves them.

8. What changes for developers

If Mythos does what the benchmarks suggest, the impact for developers will be profound across several dimensions:

More complex projects with less supervision

Today, even with Opus 4.6 and Agent Teams, very complex projects still require constant human supervision. The developer needs to review each step, correct errors in reasoning and redirect the agent when it loses its way. With a step change in multi-hop reasoning, Mythos could run entire projects with human checkpoints only at critical milestones, not at every step.

Debugging legacy systems

Legacy codebases are every developer's nightmare. Code 10-15 years old, undocumented, with obsolete dependencies and business logic buried in layers of patches. Opus 4.6 already helps, but it is often lost in very large projects. If Mythos truly has superior code analysis capabilities at scale, it could become the ultimate tool for modernizing legacy systems.

Security as standard

Cybersecurity scores suggest that Mythos could be integrated into security pipelinesCI/CDas an automatic security auditor. Imagine a model that analyzes each pull request not just for functionality, but for security vulnerabilities, with a detection rate higher than specialized tools. This would transform security from a “final step” to a “continuous process”.

Skills and automation

For those who use Claude Code with skills, a more capable model means that each skill works better. A "create landing page" skill that today generates a good page, with Mythos could generate a page with conversion, accessibility and performance optimizations that today require human review. The skill doesn't change, but the model that executes it becomes dramatically better.

9. What changes for marketers

If you are a marketing professional and use Claude Code for your daily work, Mythos represents a significant evolution in several areas:

Deeper strategic analysis

Mythos' deep multi-hop reasoning would enable market and competition analysis with a level of sophistication that today requires entire teams. Think about asking Claude Code to analyze the positioning of 20 competitors, cross-check industry trend data, identify gaps in the market and suggest positioning strategies -- all in a single session, with end-to-end coherence.

Copy and content with more nuance

Opus 4.6 already generates quality copy. But truly exceptional copy requires a deep understanding of psychology, cultural context, and nuances of language. A step change in reasoning could produce texts that are not only grammatically correct and persuasive, but that demonstrate true understanding of the target audience and their motivations.

Smarter tracking and analytics

For those working with tracking -- GTM, Meta Pixel, GA4, CAPI --, Mythos could analyze complex tracking configurations and identify problems that currently take hours to diagnose. Consent Mode settings, discrepancies between server-side and client-side, cross-domain attribution -- all of this would be more accessible.

Report automation

Imagine giving Claude Code access to your analytics accounts and asking for a weekly report that not only presents numbers, but analyzes trends, identifies anomalies, and suggests corrective actions. Opus 4.6 already does this reasonably, but with gaps in in-depth analysis. Mythos could be the model that finally makes automated reports as good as those done manually by senior analysts.

10. Impact on the skills and automation market

The launch of Mythos will have a ripple effect on the ecosystem of tools built around Claude Code:

Existing skills become more powerful

A skill is, in essence, a set of instructions that the model follows. When the model that executes these instructions improves drastically, each skill automatically benefits. Minhaskills.io's 748+ professional skill packs, for example, were written to work with Sonnet and Opus. With Mythos, these same skills would produce significantly superior results without any necessary upgrades.

New skill categories become viable

There are tasks that today do not work well as skills because the model cannot execute them consistently. Complete security audit skills, in-depth financial analysis, or long-term strategic planning. With Mythos, these categories become viable, expanding the skills market considerably.

More sophisticated Agent Teams

Opus 4.6's Agent Teams feature allows you to coordinate multiple sub-agents. With Mythos as a base model, these teams of agents could handle much more complex projects. Imagine an Agent Team that receives a campaign briefing and delivers ads, landing pages, tracking configuration and metrics reports -- all coordinated automatically.

The gap between those who use and those who do not use increases

Each new model expands the advantage of early AI adopters. Professionals who already use Claude Code with skills will automatically benefit from Mythos. Professionals who are still in web chat or don't use AI will fall further and further behind inproductivity. The Mythos doesn't create this dynamic -- it accelerates it.

11. How to prepare for Mythos

Even without a confirmed release date, there are concrete actions you can take now to be ready when Mythos arrives:

Master the Claude Code today

Mythos will run on Claude Code (or an updated version of it). If you already master the tool -- commands, skills, CLAUDE.md, workflows --, the transition will be instantaneous. If you don't already use it, start now. The learning curve is invested once and applies to all future models.

Invest in skills

Skills are investments that increase in value with each new model. A skill you buy or create today will work better when Mythos arrives, at no additional cost. The more skills you have in your arsenal, the more you benefit from each model upgrade.

Document your workflows

Your project's CLAUDE.md file is the link between you and the model. The better documented your workflow, the better any future model will perform its tasks. Invest time now in creating detailed CLAUDE.md for your projects.

Follow official channels

Anthropic announces new models on the official blog (anthropic.com/news) and on Twitter/X (@AnthropicAI). Historically, they give little advance notice -- Opus 4.6 was announced and released on the same day. Be careful not to lose access on day zero.

Evaluate your subscription plan

If the Mythos comes in a premium tier above Max, it may require a new plan. If you're on the Pro plan ($20/month), consider trying Max ($100-200/month) to ensure you'll have quick access when Mythos is released. Anthropic has historically prioritized higher plans when rolling out new models.