However, on April 16, 2026, Anthropic released Claude Opus 4.7, a public model that beats Opus 4.6 across coding, reasoning, and agentic tests while quietly trailing the company's still-private Mythos preview. However, however, if you build with Claude or pay for Claude Code, the question you actually need answered is simple: do you upgrade today, or wait for Mythos? This guide compares Claude Opus 4.7 to Mythos head-to-head across pricing, context window, SWE-bench scores, and real coding workflows, so you can decide in five minutes.
Key Takeaways
- Claude Opus 4.7 is public. Mythos is still a private preview gated to Project Glasswing partners.
- Pricing is identical to Opus 4.6 at $5 per million input tokens and $25 per million output tokens, but a new tokenizer can raise actual spend by 1.0–1.35x.
- Opus 4.7 hits 87.6% on SWE-bench Verified and 64.3% on SWE-bench Pro. In contrast, strong, but Mythos posts roughly 93.9% on SWE-bench Verified.
- The 1M context window and 2x agentic throughput are the headline upgrades for engineering teams already paying for Claude.
Table of Contents
- Claude Opus 4.7 Explained
- Comparing Opus 4.7 vs Mythos: Real Differences
- Benchmark Scores for Opus 4.7
- Pricing and Token Counts of Opus 4.7
- Fresh Features in Opus 4.7
- Picking Between Opus 4.7 and Mythos
- Accessing Opus 4.7
What Is Opus 4.7?
Opus 4.7 is Anthropic's most powerful public model as of April 16, 2026. It replaces Opus 4.6 at the top of the public Claude lineup and ships with the same $5/$25 pricing, the same 1M-token context window, and a new tokenizer. As a result, according to Anthropic, Opus 4.7 outperforms Opus 4.6 across agentic coding, multidisciplinary reasoning, and tool use.
However, the launch arrives during a busy month for Anthropic. On the other hand, google announced an investment of up to $40 billion in the company on April 24. 2026, with $10 billion committed up front. Yearly revenue reportedly reached $30 billion. Still, still, up from $9 billion at the end of 2025.
For example, if you have used Claude inside Cursor, Claude Code, or Anthropic's API in the last quarter, Opus 4.7 is the upgrade you get when you switch your model string to claude-opus-4-7. No new account, no new pricing tier.
Quick facts about Opus 4.7
In contrast, here is what changed compared to Opus 4.6:
- 1M-token context window (input), 128K output (unchanged from 4.6)
- Image input now supports up to 2,576 pixels on the long edge. So, more than 3x earlier Claude models
- 2x agentic throughput compared to Opus 4.6
- Image vision tests up across charts, screenshots, and diagrams
- Same $5 per 1M input tokens and $25 per 1M output tokens
Opus 4.7 vs Mythos: The Real Differences
The honest framing is that Mythos is a research preview, not a public product. Anthropic has only deployed Mythos to a small group of partners through a cybersecurity initiative called Project Glasswing. In fact, you cannot buy Mythos through the standard Claude API, and Anthropic has not announced a general release date.
For example, that said, the two models target different jobs. Now however, opus 4.7 is the safe. Scaled version Anthropic feels comfortable shipping to every developer. Mythos pushes power further but carries cyber-risk concerns Anthropic is still working through.
The power gap
As a result, according to Anthropic's own announcement. In contrast, in contrast, mythos beats Opus 4.7 on long-context reasoning. Agentic computer-use tasks,. Software engineering. The published numbers from third-party comparisons line up with that: Opus 4.7 lands at 87.6% on SWE-bench Verified. On the other hand, while Mythos sits near 93.9%. For instance, roughly a 6-point lead.
In contrast, mythos is also positioned as a higher-stakes model from a safety angle. Still, anthropic just reduced Opus 4.7's cyber powers during training. Added automatic detection that blocks high-risk security requests. So, mythos has fewer such guardrails. Which is why it is gated to verified partners.
When does the Mythos gap matter?
As a result, for most engineering teams, the gap is small enough to ignore. If you are using Claude for daily coding, refactoring, code review, or pull-request automation, Opus 4.7 is the right choice today. The Mythos lead shows up mainly on multi-hour agentic tasks, deep code-base reasoning, and security research where every percentage point matters.
On the other hand, have you actually hit the ceiling on Opus 4.6 in the last month? If the answer is no, Opus 4.7 is more than enough.
Opus 4.7 Benchmark Scores Explained
For instance, tests tell only part of the story. But they anchor the match-up. So, here are the public numbers from Anthropic and third-party testing labs.
SWE-bench results
On the other hand, according to Vellum's benchmark breakdown, Opus 4.7 leads on the standard SWE-bench tests:
- Verified score on SWE-bench: 87.6% (Opus 4.7) vs 80.6% (GPT-5.4)
- Pro score on SWE-bench: 64.3% (Opus 4.7) vs 54.2% (GPT-5.4)
- Mythos result on SWE-bench Verified: about 93.9%
For instance, sWE-bench Verified measures the percentage of real GitHub issues a model can resolve end-to-end with no human intervention. A 7-point lead over GPT-5.4 is meaningful for production agents that need to reliably ship a pull request.
Agentic and tool-use scores
Still, anthropic reports that Opus 4.7 delivers 2x agentic throughput compared to Opus 4.6 on the same hardware. For example, that comes from better tool selection, fewer wasted tool calls,. However, faster reasoning on long traces. Engineering teams running Claude Code workflows reported noticeable speedups within the first 48 hours.
Vision tasks
The most underrated upgrade is image input resolution. Opus 4.7 accepts images up to 2,576 pixels on the long edge. In contrast, on the other hand, more than three times the resolution earlier Claude models accepted. This matters for reading dense charts, processing high-quality screenshots, or pulling numbers from diagrams.
Opus 4.7 Pricing and Token Counts
Yet, the headline number stayed flat. On the other hand, anthropic kept Opus 4.7 priced at $5 per million input tokens and $25 per million output tokens, the same as Opus 4.6. Yet, cached input tokens stay at $0.50 per million.
The hidden cost: a new tokenizer
So, here is the part that did not make most launch headlines. Still, opus 4.7 ships with an updated tokenizer that increases the token count for the same English text by 1.0 to 1.35x, depending on content type. Per Finout's pricing analysis, that translates to a real-world spend increase of roughly 5–25% on the same workloads, even though the per-token price did not change.
In fact, if you run high-volume Claude workloads. Run a sample of last week's prompts through both tokenizers. So, however, compare. Most teams will see a small but real cost bump.
A real cost example
But a 20,000-token prompt with a 4,000-token response on Opus 4.6 costs roughly $0.20. However, the same task on Opus 4.7. After factoring a 1.2x tokenizer increase, costs about $0.24. As a result, a 20% jump for an identical user-visible request.
New Features in Opus 4.7
Still, beyond raw scores. Opus 4.7 ships several behavior changes that matter day to day.
Better instruction following
Opus 4.7 is noticeably more obedient. Earlier Claude models sometimes ignored a system prompt rule when a user message contradicted it. Then in contrast, the new model holds the original instruction more reliably, which matters for agent harnesses where the system prompt encodes safety rules.
Cyber power safeguards
Even so, anthropic just reduced Opus 4.7's cyber powers during training. The model now on its own detects. On the other hand, still. Blocks requests that look like prohibited or high-risk security work. Researchers running legitimate offensive security work can apply through a formal verification program to access expanded powers.
Amazon Bedrock access
However, opus 4.7 launched on Amazon Bedrock the same day. AWS users get the same pricing through Bedrock. Still, in fact, can use Claude with private VPC routing. AWS PrivateLink, and Bedrock Guardrails. If your stack already runs on AWS. This is the path of least resistance.
Claude Code speed
For example, claude Code. In contrast, anthropic's CLI for AI-assisted engineering. Defaults to Opus 4.7 from launch day. So, internal tests show roughly 2x faster end-to-end task completion compared to Opus 4.6 on long agentic runs. Meaningful when you are paying for compute time on a 4-hour refactor.
When to Pick Opus 4.7 vs Mythos
Yet, since Mythos is gated, the practical question is when to wait for it versus when to ship on Opus 4.7 today.
Pick Opus 4.7 if:
- You build production features that need a stable, well-understood model.
- Your work fits inside the standard cyber and content guardrails.
- You want a 1M context window, fast agentic loops, and same-as-before pricing.
- You ship code with Claude Code or Cursor every day.
Wait for Mythos if:
- You are doing legitimate offensive security research and have applied to Project Glasswing.
- Your workload is dominated by extremely long-context reasoning where 6 SWE-bench points matters.
- You are willing to wait an no set amount of time for general access.
However, for 95% of engineering teams, Opus 4.7 is the right call today. Shipping with the available model beats waiting for the perfect one.
How to Access Opus 4.7
For example, three paths cover almost every developer.
Anthropic API
In contrast, set your model string to claude-opus-4-7 in your existing Anthropic API client. However, for instance, no version migration script, no breaking changes from Opus 4.6 in standard text gen. Re-test agent harnesses to take advantage of the 2x throughput.
Claude apps and Claude.ai
In contrast, pro and Max subs see Opus 4.7 in the model picker by default. In contrast, free users still get Sonnet-level power for daily chat.
Amazon Bedrock and Google Cloud Vertex AI
As a result, opus 4.7 is available on Bedrock through the Anthropic provider. Here, so, vertex AI users get it through Anthropic's Vertex integration. Both routes carry identical pricing.
On the other hand, if you want a deeper look at Anthropic's broader agent strategy, our guide on Agentic AI in 2026 walks through how these models slot into a production agent stack.
Summary
For instance, claude Opus 4.7 is the right Claude model for almost every developer today. On the other hand, it matches Opus 4.6 pricing. Ships a 1M context window. For example, doubles agentic throughput, and beats GPT-5.4 on SWE-bench Verified. Still, mythos is more powerful on paper but is locked to Project Glasswing partners. Is not a general option. So, on the other hand, switch your model string. Watch your tokenizer cost, and ship.
Frequently Asked Questions
Is Opus 4.7 better than GPT-5.4?
Still, on software engineering tests, yes. Opus 4.7 scores 87.6% on SWE-bench Verified versus 80.6% for GPT-5.4. However, leads on SWE-bench Pro by roughly 10 points. Yet, for non-engineering tasks the gap is narrower. Depends on the workload.
How much does Opus 4.7 cost per 1M tokens?
Yet, claude Opus 4.7 costs $5 per million input tokens. $25 per million output tokens. In contrast, identical to Opus 4.6. Cached input tokens are $0.50 per million. On the other hand, however, the new tokenizer can increase total tokens billed by 1.0 to 1.35x for the same English text.
Can I access Claude Mythos right now?
So, no. Mythos is a private preview deployed only to partners in Anthropic's Project Glasswing cybersecurity initiative. Still, anthropic has not announced a general access date for Mythos.
Does Opus 4.7 work with Claude Code?
In fact, yes. As a result, claude Code defaults to Opus 4.7 from launch day,. Internal tests show roughly 2x faster end-to-end task completion compared to Opus 4.6 on long agentic engineering runs.
What is the context window for Opus 4.7?
But claude Opus 4.7 supports a 1 million-token input context window with up to 128K output tokens. So, the same as Opus 4.6. Image input resolution increased to 2,576 pixels on the long edge.
Editorial Disclosure: This article was researched and drafted with AI assistance, then reviewed, fact-checked, and edited by Bhanu Prakash to ensure accuracy and provide hands-on insights from real-world experience.
About the Author
Bhanu Prakash is a cybersecurity and cloud computing professional with hands-on experience working with large language model APIs, AI agent stacks, and developer tooling. However, still, he shares practical guides and career advice at ElevateWithB.
What to Read Next: Take the next step with our deep dive on AI Agent Security Threats in 2026 and learn how Opus 4.7 fits into a hardened agent stack.
