Claude Opus 4.7: Anthropic’s Flagship Model Explained (2026 Guide)

What it is: Claude Opus 4.7 is Anthropic’s flagship publicly available large language model, released April 16, 2026 as the successor to Opus 4.6. It keeps the 1M-token context window (beta), adds a new “xhigh” effort level between high and max, ~3x improves vision input resolution (to 2,576 pixels / 3.75 megapixels), and leads SWE-bench Pro at 64.3% for multi-file software engineering. Pricing is unchanged from Opus 4.6: $5 / $25 per million tokens (input / output).
Who it is for: Developers handing off complex coding work, knowledge workers running long-context analysis, founders running agentic workflows, and researchers who need the strongest available Claude for difficult reasoning.
Best if: You hit the ceiling on Opus 4.6 for the hardest coding tasks, want the new xhigh effort level, or need substantially better image understanding.
Skip if: Your tasks are short, simple, or latency-sensitive — Sonnet 4.6 is roughly 5x cheaper and faster. Daily AI fundamentals in our free Beginners in AI newsletter.

Claude Opus 4.7 went generally available on April 16, 2026. It is currently Anthropic’s most capable publicly accessible model, the direct successor to Opus 4.6 (February 5, 2026), and the daily-driver Opus model for serious software engineering, agentic work, and long-context tasks.

Here’s what changed from 4.6, what Opus 4.7 actually does well in 2026, and when to reach for it versus Sonnet 4.6 or GPT-5.5.

What is the bottom line on Claude Opus 4.7?

• Best generally available Claude for hard work. Coding, complex reasoning, long-context analysis, multi-step agent loops.
• Same price as Opus 4.6. $5 / $25 per million tokens. Anthropic held the price line through the upgrade.
• Substantially better vision. Image input resolution went from ~1.15 MP to ~3.75 MP — roughly 3x the pixels Claude can process per image.
• New xhigh effort level. Sits between high and max. Lets you dial in finer reasoning-vs-latency tradeoffs.
• 1M-token context (beta) carried forward from 4.6. The single biggest workflow-changing capability for long-document work.
• Leads SWE-bench Pro at 64.3%. Best public-benchmark result for multi-file software engineering as of April 2026.
• Not perfect. GPT-5.5 leads on agentic computer-use benchmarks (Terminal-Bench 2.0, OSWorld-Verified). Anthropic has acknowledged that an unreleased internal model called Mythos still outperforms Opus 4.7 internally.

What is Claude Opus 4.7 exactly?

Claude Opus 4.7 is the most capable generally available model in Anthropic’s lineup. It sits at the top of the Anthropic family:

• Opus 4.7 — flagship; hardest tasks; deepest reasoning
• Sonnet 4.6 — balanced; lower cost; faster; most production work
• Haiku 4.5 — smallest; fastest; cheapest; bulk processing and short tasks

Opus 4.7 was released April 16, 2026 as the direct successor to Opus 4.6 (Feb 5, 2026), which itself replaced Opus 4.5. Anthropic’s recent cadence has been a new Opus model every roughly 2–3 months, each with measurable benchmark gains over its predecessor.

What is new in Claude Opus 4.7 versus Opus 4.6?

Capability	Opus 4.6	Opus 4.7
Release date	February 5, 2026	April 16, 2026
Context window	1M tokens (beta)	1M tokens (beta)
Pricing (input / output per 1M tokens)	$5 / $25	$5 / $25 (unchanged)
Effort levels	Low / medium / high / max	Low / medium / high / xhigh / max
Max image input resolution	1,568 px long edge (~1.15 MP)	2,576 px long edge (~3.75 MP)
SWE-bench Pro	(prior best)	64.3% (current best)
Internal 93-task coding benchmark	Baseline	+13% over 4.6, including 4 tasks neither 4.6 nor Sonnet 4.6 could solve
Use case fit	Daily-driver flagship	Drop-in upgrade for hardest tasks

The 4.7 release is intentionally a focused upgrade rather than a re-architected model. The headline gain is on the hardest software-engineering tasks — the kind that previously needed close supervision now ship with confidence using Opus 4.7. Vision capability got the most dramatic numeric improvement (3x pixels). The xhigh effort level is a small but useful refinement for users who want one more notch between high and max.

How much does Claude Opus 4.7 cost?

• API pricing: $5 per million input tokens, $25 per million output tokens. Unchanged from Opus 4.6.
• Prompt caching: Substantial discounts available for repeated context, particularly useful for long-context (1M-token) workflows. Up to 90% off on cached input.
• Batch processing: 50% off both input and output when using the Anthropic Message Batches API.
• Claude.ai (Pro / Max / Team plans): Opus 4.7 access included with usage limits that scale by plan.
• Claude Code: Opus 4.7 access included via the same Claude.ai subscription, plus per-token API metering for heavy use.
• Third-party platforms: Available through Amazon Bedrock, Google Vertex AI, and the Anthropic API directly. Bedrock and Vertex pricing closely matches Anthropic’s.

Cost discipline is one of the more interesting things about the 4.6 → 4.7 cycle. Anthropic delivered a measurably stronger model and held the same pricing, which is the opposite of how most flagship-model upgrades have gone in the industry over the past two years.

When should you use Opus 4.7 versus Sonnet 4.6?

Sonnet 4.6 remains the workhorse. The decision rule:

• Use Sonnet 4.6 for: Most production work. Web app inference. Latency-sensitive workflows. Short or medium-length tasks. Bulk processing where cost per request matters. The 80/20 of most teams’ day-to-day usage.
• Use Opus 4.7 for: Complex coding tasks Sonnet has been failing on. Long-document analysis (especially with 1M context). Multi-step agentic workflows where one mistake compounds. Hard reasoning problems. Tasks where a 5x cost premium is justified by the quality lift.
• Use Haiku 4.5 for: Cheap bulk processing. Classification. Short-answer Q&A. High-throughput pipelines.

The economic reality: Opus 4.7 is roughly 5x the price of Sonnet 4.6. A team running 1M Sonnet requests a month at average cost is looking at thousands of dollars; the same workload on Opus 4.7 is tens of thousands. Use Opus where it genuinely changes the outcome; route everything else to Sonnet.

What is the new xhigh effort level?

Anthropic’s adaptive-thinking effort levels let the user control how much reasoning the model does before answering. Higher effort means more internal thinking, better answers on hard problems, but slower latency and higher token cost.

With 4.7 the family expanded:

• Low — minimal reasoning; fast; chat-style use.
• Medium — default for most tasks; reasonable depth and latency.
• High — deeper reasoning for hard problems.
• Xhigh (new in 4.7) — one notch above high; deeper still but without going all the way to max.
• Max — longest internal reasoning; best for the hardest problems where latency doesn’t matter.

The xhigh slot was added because Anthropic observed users wanting a setting between high and max that gave most of the reasoning depth without the full latency hit of max. For agentic coding loops where you might call the model thousands of times, that difference compounds.

How does the 1M-token context window work?

Opus 4.7 retains the 1-million-token context window that arrived in Opus 4.6. The capability is still labeled beta and access is gated — some accounts have it enabled by default, others need to request access through Anthropic.

What 1M tokens lets you do:

• Load an entire mid-sized codebase (~50,000–100,000 lines of source) into a single context.
• Analyze book-length documents in one pass without chunking.
• Run multi-hour agent loops where the prior 50 turns stay in context.
• Compare 20+ research papers, contracts, or RFPs simultaneously.
• Maintain durable working memory across long sessions.

What 1M tokens does not solve:

• Cost — loading 800,000 tokens of context every turn gets expensive fast. Prompt caching mitigates substantially but not entirely.
• Latency — longer contexts produce slower responses. Plan for 30s–90s first-token times on full 1M-context requests.
• Quality at extremes — performance is strongest when context fits within ~200K–500K tokens. Pushing to 800K+ is reliable but not magic; the model still tends to attend more strongly to recent and to leading sections.

How does Opus 4.7 compare to GPT-5.5?

The honest comparison in May 2026:

Benchmark / capability	Opus 4.7	GPT-5.5	Winner
SWE-bench Pro (multi-file coding)	64.3%	58.6%	Opus 4.7
Terminal-Bench 2.0 (agentic terminal use)	69.4%	82.7%	GPT-5.5
OSWorld-Verified (computer-use)	78.0%	78.7%	~Tied (slight GPT-5.5 edge)
1M-token context	Yes (beta)	Yes (varies by tier)	Comparable
Vision input resolution	2,576 px (3.75 MP)	~comparable	Comparable
API price per 1M output tokens	$25	~$15–$30 (tier-dependent)	Depends on tier

The model-by-model picture: Opus 4.7 leads on traditional software-engineering benchmarks. GPT-5.5 leads on agentic-computer-use tasks. Most teams in production end up using both for different work types rather than picking a single winner.

What is Mythos and how does it relate to Opus 4.7?

Mythos is an internal Anthropic model that, by Anthropic’s own acknowledgment at the time of the Opus 4.7 release, outperformed 4.7 on internal evaluations. Anthropic chose to release Opus 4.7 publicly while continuing to safety-test and refine Mythos.

The reasoning Anthropic publicly gave: Mythos hadn’t cleared the company’s Responsible Scaling Policy safety bar for public release. Opus 4.7 represents what Anthropic considers safe to ship in May 2026. Mythos is the rough preview of what the next-generation public release (Opus 5 or similar naming) will look like once safety work concludes.

For more on Mythos, see our coverage of the Claude Mythos & Apple M5 security exploit story.

How do you access Claude Opus 4.7?

• Claude.ai — Pro, Max, and Team plans include Opus 4.7 access. Free tier is gated to Sonnet/Haiku.
• Anthropic API — direct API access. Model name typically `claude-opus-4-7` or the date-stamped variant used in API calls.
• Amazon Bedrock — available across most Bedrock regions. Same pricing structure as Anthropic direct.
• Google Vertex AI — available in supported Vertex regions.
• Claude Code — the Anthropic CLI for software engineering. Opus 4.7 is the default model on the higher subscription tiers.
• GitHub Copilot — Claude Opus 4.7 became generally available on Copilot on April 16, 2026, the same day Anthropic announced the model.
• Cursor, Windsurf, and other Claude-supporting IDEs — updated to Opus 4.7 within days of release.

What about Claude Skills and Agent Skills on Opus 4.7?

Claude Skills — reusable instruction sets that travel with the user across conversations — work with Opus 4.7. The format Claude Skills introduced in early 2026 is unchanged; Opus 4.7 just applies the skill faster and more reliably.

For agent workflows on Claude Code, Opus 4.7’s 13% improvement on Anthropic’s internal 93-task coding benchmark is the metric that matters most. The improvement compounds over multi-step agent loops — an agent that makes a 13% better decision at each step ends a 10-step loop in a substantially better state than its predecessor.

Frequently asked questions

When was Claude Opus 4.7 released?

April 16, 2026. Generally available on the same day on the Anthropic API, Claude.ai, Bedrock, Vertex, GitHub Copilot, and most major Claude-supporting tools.

Is Opus 4.7 better than Opus 4.6?

Yes, by Anthropic’s own benchmarks and by the prevailing user assessment. On Anthropic’s internal 93-task coding benchmark Opus 4.7 outperforms Opus 4.6 by 13%, including solving four tasks neither Opus 4.6 nor Sonnet 4.6 could solve. SWE-bench Pro improvement from prior best to 64.3% is the public-benchmark expression of the same gain.

Should I upgrade my application from Opus 4.6 to Opus 4.7?

Almost always yes if you’re currently calling Opus 4.6. The pricing is identical and the capability is strictly better on the workloads Opus is suited for. The only reason to delay is if you have rigorous evaluations of 4.6 in production that you haven’t re-run against 4.7 yet.

What is the model name in the API?

The current model ID is `claude-opus-4-7`. Anthropic also publishes date-stamped variants for production pinning (e.g. `claude-opus-4-7-YYYYMMDD`) that don’t change underneath you when newer versions release.

Does Opus 4.7 have a vision-only or text-only mode?

No. Opus 4.7 is multimodal — it accepts text and images natively in the same request. You don’t toggle between modes; you just include images in the user message and the model handles both.

Can Opus 4.7 generate images?

No. Opus 4.7 reads images but does not produce them. For image generation use a dedicated image model (DALL-E 3, GPT-image-1, Midjourney, Imagen 3, Stable Diffusion variants).

What’s coming after Opus 4.7?

Anthropic hasn’t publicly committed to a next release date. The internal Mythos model is the rough preview of the next-generation Opus class. Realistic expectations: a successor Opus model sometime in the next 2–4 months, continuing Anthropic’s recent cadence of focused releases.

The bottom line

Claude Opus 4.7 is the strongest publicly available Claude model in May 2026. It’s a focused upgrade on Opus 4.6 with the same pricing, a meaningful coding-benchmark gain, a new xhigh effort level, and 3x improved vision input resolution. For teams already running Opus 4.6 in production, the upgrade is essentially free in cost terms and clearly positive in capability terms.

The realistic deployment pattern: use Opus 4.7 for the hardest 20% of your workload where quality matters most, route everything else to Sonnet 4.6 for cost and latency reasons, and keep Haiku 4.5 for bulk classification and high-throughput pipelines.

For broader context: Claude Opus 4.6 Overview, Every AI Model Worth Knowing in 2026, Anthropic Company Guide, How to Use Claude AI: The Complete Beginner’s Guide. Daily AI fundamentals in our free Beginners in AI newsletter.

Sources

• Anthropic, Introducing Claude Opus 4.7 (April 16, 2026).
• Anthropic, Claude Opus product page — current model documentation.
• GitHub Changelog, Claude Opus 4.7 is generally available.
• Axios, Anthropic releases Claude Opus 4.7, concedes it trails unreleased Mythos.
• CNBC, Anthropic releases Claude Opus 4.7, a less risky model than Mythos.
• Verdent, Claude Opus 4.7: What Changed for Coding Agents.
• Anthropic API documentation — pricing, prompt caching, batch processing details.
• SWE-bench Pro leaderboard — benchmark results as of April–May 2026.

You May Also Like

• Claude Opus 4.6: Predecessor Model Explained
• Every AI Model Worth Knowing in 2026
• Anthropic Company Guide
• How to Use Claude AI: The Complete Beginner’s Guide
• Claude Mythos and the Apple M5 Security Exploit