AI-First
Anthropic charges $25 per million input tokens and $125 per million output tokens for its Claude Mythos Preview model. That is five times the price of Opus 4.6, the model that served as the benchmark until now. The figure has been circulating on technical forums since the April 8, 2026 announcement, and the same question keeps coming up: should you budget for Mythos in your AI project, or stick with Opus?
I have been helping SMBs integrate Claude for over a year. My short answer: Mythos is not built for you. The long answer requires laying the real numbers on the table, comparing benchmarks, and separating raw performance from actual value for a business leader.
- 💰 5x the price of Opus: Mythos charges $25/$125 per MTok versus $5/$25 for Opus 4.6.
- 🔒 Restricted access: limited to partners in the Glasswing program (AWS, Google, Microsoft).
- 📊 Record benchmarks: 77.8% on SWE-Bench Pro, 82% on Terminal-Bench 2.0.
- 🎯 SMB verdict: Opus or Sonnet cover 95% of business use cases at a fraction of the cost.
Here is the full Claude pricing comparison, the benchmarks that matter, and the reasoning behind my verdict.
What Claude Mythos actually costs in May 2026
The Mythos pricing does not yet appear on the official Anthropic pricing page. The figures come from data shared by Glasswing program partners and confirmed by the technical community on r/accelerate: $25 per million input tokens, $125 per million output tokens.
To put that number in concrete terms: a request with 10,000 input tokens and 2,000 output tokens costs $0.50 with Mythos. The same request on Opus 4.6 comes to $0.10. Multiply by 500 daily requests (a typical pace for an autonomous agent), and the bill jumps from $50 to $250 per day. Over a month, the gap exceeds $6,000.
Why is Mythos priced so high?
Mythos belongs to the Capybara tier, a new level above Opus in the Anthropic hierarchy. According to analysis from claudemythosai.io, pre-launch materials describe Capybara as "larger and smarter than our Opus models, which were previously our most powerful." A larger model consumes more GPU power per inference. The compute cost passes directly through to the API price.
Anthropic has also restricted access to members of the Glasswing program, a $100 million defensive cybersecurity initiative bringing together AWS, Apple, Google, Microsoft, NVIDIA, CrowdStrike, JPMorgan Chase, and the Linux Foundation. The positioning is clear: Mythos targets critical security use cases, not general-purpose usage.
The access restriction also creates a scarcity effect. As long as Mythos remains internal, Anthropic controls inference volumes and avoids overloading infrastructure that is already under strain. If you want to understand the full reasoning behind this choice, I covered the topic in detail in 5 reasons why Claude Mythos is not public.
The complete Claude pricing grid in May 2026
Before judging whether Mythos is worth its price, you need to see the full lineup. Anthropic offers four distinct tiers (Haiku, Sonnet, Opus, Capybara), each calibrated for a specific type of workload. The classic trap: picking the most powerful model by reflex, when the cheapest model capable of solving the problem is almost always the right choice.
How to choose between Haiku, Sonnet, Opus, and Mythos?
The decision comes down to two criteria: task complexity and request volume. A customer support chatbot does not need the same brainpower as an agent auditing production code.
| Model | Input ($/MTok) | Output ($/MTok) | Context | Typical use case |
|---|---|---|---|---|
| Haiku 4.5 | 1 | 5 | 200K tokens | High-volume APIs, triage, prototyping |
| Sonnet 4.6 | 3 | 15 | 200K tokens | Code, writing, daily use |
| Opus 4.6 / 4.7 | 5 | 25 | 200K tokens | Complex reasoning, agents, planning |
| Mythos Preview | 25 | 125 | Undisclosed | Cybersecurity, cutting-edge research |
SOURCE: platform.claude.com + Glasswing partner data · Updated 05/2026
The point this table makes obvious: Opus 4.7 costs exactly the same as Opus 4.6 ($5/$25 per MTok), while offering an optimized tokenizer that improves performance across a wide range of tasks. If you are still on an earlier version, migrating to 4.7 is a free performance upgrade.
On the consumer subscription side, pricing has not changed since early 2026: Claude Pro at $17/month (roughly €20/month billed monthly), Max between $100 and $200/month depending on intensity. Claude Code and Cowork are included in all paid plans (Pro, Max, Team, and Enterprise) at no extra charge. According to the plateya.fr guide, "for the vast majority of freelancers and small business owners, Claude Pro is enough."
For an SMB of 10 to 50 people, a realistic AI budget runs $200 to $600/month, not $6,000.
Mythos vs Opus: do the benchmarks justify the price gap?
The raw numbers are impressive, no question. On SWE-Bench Pro (fixing bugs in real open-source code), Mythos reaches 77.8%. On Terminal-Bench 2.0 (command-line tasks), it scores 82%. On HLE, a complex reasoning benchmark without tools, it achieves 56.8%. And on ScreenSpot-Pro (interacting with tiny UI elements), it climbs to 92.8%.
These results put Mythos in a class of its own. According to claudemythosai.io, it "significantly outperforms Opus 4.6 across all major benchmarks." Not some of them, all of them. The word "significantly" is chosen carefully by Anthropic.
What use cases make Mythos relevant?
The answer centers on one domain: advanced cybersecurity. The most striking demonstration remains the 90-minute attack chain during which Mythos identified and exploited a 20-year-old zero-day in the Linux kernel. On the "Firefox 147 JS Shell exploitation" benchmark, it reaches 84% compared to 15.2% for Opus 4.6. The gap is not incremental; it is categorical.
A contributor on r/accelerate adds an important nuance, however: "Opus 4.6 actually found the crashes first, and Mythos was given the crash categories to develop the exploit. It is more of an expert triage tool than an autonomous zero-day hunter." The nuance matters: Mythos excels at targeted exploitation, not necessarily at autonomous detection.
For everyday coding (outside vulnerability exploitation), the community reports an average 4x productivity gain with Mythos over Opus. The figure sounds spectacular. The same Reddit thread points out, however, that you would need a 40x productivity gain to offset a 5x higher cost at comparable volume. The math only works if each individual request has very high unit value, which is the case in cybersecurity, not in CRM automation.
How does Mythos actually differ from Opus 4.7?
A common source of confusion: Mythos is not "a better Opus 4.7." Opus 4.7 stays in the Opus tier at $5/$25 per MTok. Mythos inaugurates the Capybara tier. These are two distinct performance classes, like comparing a reliable workhorse to a race car. The race car wins on the track, but the workhorse handles 90% of daily trips just fine.
I also published a comprehensive guide on Claude Mythos covering the technical architecture, validated use cases, and the reasons Anthropic maintains the access restriction.
"The real value is not in the model, but in the integration with business processes. A well-connected Haiku creates more value than a Mythos running in a demo."
Vincent, May 2026
What I recommend to my SMB clients
I have helped dozens of SMBs choose their AI stack this year. Not a single one needed Mythos. The pattern I see everywhere: a business leader reads an article about the "latest and most powerful model," wants to integrate it, then we lay out the numbers and realize that the real cost of LLMs hides in request volume, not in the model's unit price.
Should you wait for Mythos before launching an AI project?
No. Waiting for Mythos to automate your CRM or generate your reports is like renting a crane to move a piece of furniture. Sonnet 4.6 at $3/$15 per MTok covers writing, code, and document analysis. Opus 4.6 at $5/$25 handles autonomous agents, multi-step reasoning, and complex planning.
According to the OECD AI Observatory, France ranks among the top ten countries in AI investment. The SMBs capturing that value are not the ones using the most expensive model. They are the ones that integrate the right model into the right workflow, with clear, measurable use cases.
I have seen automations running on Haiku at $1/MTok generate more margin than proof-of-concept projects on Opus, simply because Haiku ran 24/7 on a specific use case (email sorting, invoice data extraction, support ticket classification). Value comes from continuous execution, not from the model's raw power. That is also the logic I apply in the projects I lead through GoLive Software: start with the process that costs the most in human time, automate it with the cheapest model that gets the job done, measure, iterate.
My advice for business leaders reading this: first identify where your company is wasting time, choose the cheapest model capable of solving that problem, then measure the actual ROI.
If your needs ever outgrow Opus (advanced security auditing, vulnerability exploitation research, critical code analysis requiring very high reliability), you will know Mythos exists. For the remaining 95% of cases, Opus and Sonnet do the job at one fifth of the price. The question was never "which model is the best?" but "which model solves my problem at the best cost?".
Frequently asked questions
What is the exact price of Claude Mythos in May 2026?
Claude Mythos Preview is priced at $25 per million input tokens and $125 per million output tokens. These rates come from Glasswing program partner data and the technical community. Anthropic has not yet published an official pricing grid for this model on its pricing page.
Is Claude Mythos available to the general public?
No. As of May 2026, access remains limited to selected partners within the Glasswing program. These include AWS, Apple, Google, Microsoft, NVIDIA, CrowdStrike, JPMorgan Chase, and the Linux Foundation. Anthropic has not announced a general availability date.
What is the difference between Opus 4.7 and Mythos?
Opus 4.7 belongs to the Opus tier and costs $5/$25 per MTok, with an improved tokenizer compared to earlier versions. Mythos belongs to the Capybara tier, a higher performance class priced at five times the cost. They are two distinct products targeting different use cases: Opus for reasoning and agents, Mythos for cybersecurity and advanced research.
Claude Pro or Claude Max for an SMB?
Claude Pro at $17/month per user is enough for the majority of professional use cases (writing, analysis, light coding). Claude Max at $100 to $200/month is only justified for intensive technical users (senior developers, researchers, data analysts) who consume high token volumes every day. Both plans include Claude Code and Cowork at no extra charge.
Should you use the API or a Claude subscription?
For interactive human use (chat, document analysis, brainstorming), a Pro or Max subscription is simpler and more predictable. The API, billed per token consumed, is designed for automations, agents, and integrations into existing business tools. Both approaches often coexist within the same company: subscriptions for teams, API for automated workflows.