Anthropic’s recently launched Claude Opus 4.7 delivers a measurable step change in agentic coding over Opus 4.6, which shipped in February. At the same time, Anthropic’s internal Claude Mythos Preview outperforms both on frontier benchmarks yet stays locked behind Project Glasswing for defensive cybersecurity partners only. The gap between these three models shows exactly how Anthropic iterates in public while reserving its sharpest edge for controlled testing. But for coding insights, here’s a direct Claude Opus 4.7 vs Claude Opus 4.6 vs Claude Mythos comparison.

Opus 4.6: The Agentic Baseline That Changed Workflows

Claude Opus 4.6 set the baseline in February by overhauling how Claude handles long-running agentic work. It plans subtasks up front, runs tools and subagents in parallel, and maintains focus across massive codebases without drifting. Developers immediately noticed the difference in real workflows. 

The model achieved the highest score on Terminal-Bench 2.0 and led every frontier model on Humanity’s Last Exam at 53.0 percent with tools. On GDPval-AA, which tests economically valuable knowledge work in the finance and legal domains, it beat OpenAI’s GPT-5.2 by 144 Elo points and its own predecessor, Opus 4.5, by 190 points. Those numbers translated directly into fewer hand-offs for users. 

A single Opus 4.6 instance closed 13 GitHub issues and assigned 12 more across six repositories in one day. Context compaction and adaptive thinking let it keep working even when conversations pushed toward the one-million-token limit in beta. Pricing stayed at $5 per million input tokens and $25 per million output tokens, the same tier Opus models have held.

Opus 4.7: Sharper Efficiency and Real Gains

Claude Opus 4.7 builds straight on that foundation and tightens every loose screw. It ships with a new tokenizer that sometimes consumes 1x to 1.35x more tokens depending on content, yet the net result feels more efficient because the model defaults to fewer tool calls and reasons more internally. 

Low-effort mode on 4.7 roughly matches medium-effort 4.6, which means you hit high-quality output faster on everyday tasks. Third-party evaluations from Hex show a 13 percent lift in resolution rate across a 93-task coding benchmark, including four tasks that neither 4.6 nor Sonnet 4.6 could solve. The model also improved on deductive logic sections, where 4.6 occasionally stumbled and delivered the strongest long-context consistency Hex has measured. Developers who tested the preview report it cuts friction on multi-step workflows so they stay in flow instead of babysitting agents. 

Vision capabilities jumped too, with support for images up to 2,576 pixels on the long edge. Availability is immediate through claude.ai, the API as claude-opus-4-7, and all major cloud platforms. Pricing remains unchanged from 4.6.

Claude Mythos Preview: The Restricted Frontier

Claude Mythos Preview operates on an entirely different level. Released as a research preview on April 7, it is Anthropic’s most capable frontier model to date and shows striking leaps on nearly every benchmark. On SWE-bench Verified it hits 93.9 percent versus roughly 80-81 percent for Opus 4.6. CyberGym scores jump from 0.67 for 4.6 to 0.83 for Mythos. It saturates Cybench at 100 percent pass@1 and reliably develops proof-of-concept exploits for zero-days in both open-source and closed-source software. 

In one Mozilla collaboration, it exploited Firefox with four distinct bugs where 4.6 managed only one unreliable path. Mythos also solved private cyber ranges end-to-end and simulated corporate network attacks that human experts estimated would take over ten hours. Those capabilities make it invaluable for defensive work, which is exactly why Anthropic restricts access to vetted partners under Project Glasswing instead of general release. The dual-use risk is real: the same model that patches infrastructure at scale could also weaponize exploits if it fell into the wrong hands.

Claude Opus 4.7 vs Claude Opus 4.6 vs Claude Mythos: Head-to-Head Performance Breakdown

You see the progression clearly when you line up the three models side by side on practical metrics. Opus 4.6 gave developers reliable agents that could run for hours. Opus 4.7 makes those agents noticeably sharper and more efficient without changing the price. Mythos pushes the frontier so far that public release is off the table for now.

Here is how the upgrades break down in concrete terms:

• Opus 4.7 improves agentic coding resolution by 13 percent over 4.6 on Hex’s 93-task suite and solves four additional tasks that stumped the prior version.
• Low-effort 4.7 roughly equals medium-effort 4.6, letting teams dial down cost while keeping quality.
• Both 4.7 and 4.6 support the full one-million-token context window with adaptive thinking and context compaction, but 4.7 shows tighter long-context consistency and fewer drift issues.
• Mythos saturates cybersecurity evals that 4.6 only partially clears: Cybench 100 percent, CyberGym 0.83 versus 0.67.
• Mythos leads on SWE-bench Verified at 93.9 percent while 4.6 sits around 81 percent with prompt tweaks.
• Opus 4.7 clears 70 percent on CursorBench versus 58 percent for 4.6 and shows double-digit gains on Notion Agent multi-step workflows with fewer tool errors.
• All three models maintain Anthropic’s strong alignment profile, but Mythos required extra classifiers and access controls before even limited deployment.
• Vision acuity on XBOW jumps to 98.5 percent for 4.7 from 54.5 percent on 4.6.
• Opus 4.6 already led GDPval-AA with a 1606 Elo score; 4.7 builds further on finance and deductive logic modules.

The practical differences show up fastest in developer workflows. Take a senior engineer migrating a multi-million-line codebase. With Opus 4.6 she breaks the job into parallel subagents, reviews diffs, and catches her own bugs at a senior level. Opus 4.7 does the same job with 13 percent higher success rate and lower latency on low-effort settings, so she finishes the migration in half the iterations. Mythos would spot zero-days in the legacy code automatically and generate exploits or patches on the fly, but only trusted cybersecurity teams get to run those workloads.

Enterprise users notice the same pattern in knowledge work. Finance analysts using GDPval-AA style tasks get cleaner outputs and fewer hallucinations from 4.7 than from 4.6 because the model revisits reasoning more deliberately. Legal teams drafting complex contracts benefit from the same BigLaw Bench improvements that 4.6 already led. Mythos stays out of these general workflows entirely; its strengths sit in red-team simulations and infrastructure hardening where the stakes justify controlled access.

Safety teams at Anthropic also tightened the screws across the lineup. Opus 4.6 already posted the lowest over-refusal rates among recent models and added six new cybersecurity probes. Opus 4.7 inherits those safeguards plus stricter instruction-following, so it stays on task without veering into plausible but incorrect fallbacks. Mythos required the most intensive mitigations: probe classifiers for dual-use prompts, sandbox restrictions, and a 24-hour alignment testing window before any external pilot. Even then, Anthropic keeps it away from consumer platforms and limits it to defensive partners.

Claude Opus 4.7 vs Claude Opus 4.6 vs Claude Mythos: Pricing, Availability, and Real User Feedback

Pricing and availability tell the rest of the story. Both Opus 4.6 and 4.7 use the standard $5/$25 per million tokens structure. You switch to 4.7 today through the API alias claude-opus-4-7 or the latest claude.ai default for Max and Enterprise plans. Mythos does not appear in any public pricing tier. Partners access it only through Project Glasswing under strict usage policies that block offensive applications.

Real users already share early takes that line up with the benchmarks. One developer posted right after the 4.7 drop that it feels like 4.6 on steroids for long tasks. He threw the same messy migration at both and 4.7 needed half the back-and-forth while catching edge cases 4.6 glossed over. That matches the 13 percent lift and improved deductive logic scores.

The three models serve distinct roles. Most teams default to Opus 4.7 now because it delivers the best balance of intelligence, speed, and availability for coding, agents, vision, and complex professional work. Opus 4.6 remains perfectly capable and still crushes most benchmarks relative to last year’s models, so it works fine for lighter workloads or cost-sensitive projects. Claude Mythos sits in its own category: the unreleased frontier model that redefines what is possible in cybersecurity but stays behind closed doors until Anthropic decides the risk profile allows broader access.

The Bottom Line

Claude Opus 4.7 vs Claude Opus 4.6 vs Claude Mythos comes down to a simple choice between immediate capability, proven reliability, and restricted frontier power. Pick Opus 4.7 if you want the strongest generally available model right now; it ships today with clear gains in agentic coding, vision, and efficiency that make real workflows faster and less frustrating. Stick with Opus 4.6 if you already run heavy agent setups and do not need the latest edge. Reserve Mythos for the narrow set of defensive cybersecurity partners who qualify under Project Glasswing, because its zero-day discovery and exploit capabilities set a new bar that no public model touches. Anthropic keeps iterating fast, but the gap between what you can use today and what they test internally grows sharper with every release. For most users the decision is easy: upgrade to 4.7 and get more done with less effort.