Claude Opus 4.7
Anthropic flagship Claude Opus 4.7 entry for advanced reasoning, adaptive thinking, agent teams, and complex planning.
Claude Opus 4.7 is Anthropic’s most capable flagship model, setting the standard for deep reasoning, code review, and complex agent planning. It introduces adaptive thinking — automatically adjusting the compute effort per task to balance speed and accuracy — and agent teams, a multi-agent coordination system where specialized sub-agents communicate through a peer-to-peer mailbox protocol for complex multi-step problems.
With a 200,000-token standard context window (1 million tokens in beta) and very strong performance across reasoning, coding, and vision benchmarks, Opus 4.7 is the go-to choice for production workloads where answer quality and reliability are the top priority. It uses the Anthropic Messages API and is the model that pioneered MCP (Model Context Protocol) support for standardized tool integration.
For coding and code review, Opus 4.7 excels at understanding complex codebases, identifying subtle bugs, and generating well-structured solutions. For agent planning, its ability to decompose complex tasks and coordinate sub-agents makes it suitable for research, analysis, and multi-step automation where accuracy cannot be compromised for speed or cost savings. Compare with GPT-5.5 and Gemini 3.1 Pro for alternative flagship options.
| Provider | Anthropic |
|---|---|
| Context Window | 200000 |
| Pricing | Verify current pricing and context options in Anthropic docs before production use. |
| API Style | Anthropic Messages API |
| SDK | Anthropic SDK, adapter-based agent runtimes |
| MCP | Works well with MCP-based agent workflows through Anthropic-compatible clients; Claude pioneered MCP support. |
| Agent | Strong fit for planning-heavy agents, agent team coordination, review workflows, and complex reasoning tasks. |
| RAG | Suitable for source-grounded synthesis when citations and freshness are enforced. |
| Source Freshness | recently_verified |
| Version Status | current |
| Version Boundary | Claude Opus 4.7 (released May 2026) is the latest Anthropic flagship. Key upgrades include adaptive thinking for dynamic reasoning effort allocation and agent teams for multi-agent coordination with peer-to-peer mailbox protocol. 1M-token context window available in beta. |
Key Facts
- Anthropic lists Claude Opus 4.7 as its most capable model with adaptive thinking and agent teams capabilities.
- Adaptive thinking lets the model dynamically allocate compute effort per task for optimal speed and quality.
- Agent teams enable multi-agent coordination where specialized sub-agents communicate via a peer-to-peer mailbox protocol.
- 1M-token context window is available in beta.
Best For
Not Ideal For
Capability Matrix
| Capability | Status |
|---|---|
| Reasoning | Very Strong |
| Adaptive Thinking | Supported |
| Coding | Strong |
| Vision | Supported |
| Planning | Very Strong |
| Agent Teams | Supported |
SEO
| SEO Title | Claude Opus 4.7 API, Pricing, SDK, MCP & Agent Compatibility |
|---|---|
| Description | Claude Opus 4.7 by Anthropic: Anthropic flagship Claude Opus 4.7 entry for advanced reasoning, adaptive thinking, agent teams, and complex planning. |
| Canonical | /model/claude-opus-4-1 |
| Updated | 2026-05-21 |
Related Pages
Compare
| Comparison | Compared With |
|---|---|
| Claude Opus 4.7 vs Gemini 3.1 Pro | Gemini 3.1 Pro |
| Claude Opus 4.7 vs GPT-5.5 Codex | GPT-5.5 Codex |
| Claude Opus 4.7 vs GPT-5.5 | GPT-5.5 |
Compatibility Facts
| Layer | Target | Status | Evidence | Updated |
|---|---|---|---|---|
| api | anthropic-messages-api | supported | Anthropic docs and TypeScript SDK links are attached to Claude model entries. | 2026-05-18 |
FAQ
| What is Claude Opus 4.7? | Claude Opus 4.7 is listed as the Anthropic flagship model for advanced reasoning, adaptive thinking, agent teams, and planning-heavy workflows. Verify exact pricing, context options, and regional access in official Anthropic documentation. |
|---|---|
| What is Claude Opus 4.7 best for? | Claude Opus 4.7 is best for reasoning, code review, agent planning, long-form reasoning. |
| How should Claude Opus 4.7 be verified before production use? | Check current pricing, availability, limits, and API behavior against the listed official and GitHub sources. This entry was updated on 2026-05-21. |
| How are compare pages generated? | Compare pages are generated from src/content/comparisons/*.json and model frontmatter, so each comparison remains static, source-backed, and consistent with model detail pages. |
| How is model source data verified? | Each model entry must include an updatedAt value, at least one official or documentation source, at least one GitHub source, and a short citation summary for every source. |
| When should I choose a reasoning-optimized model over a general-purpose model? | Reasoning-optimized models (OpenAI o3/o4-mini, DeepSeek-V3.2) excel at math, science, multi-step analysis, and complex coding tasks where careful chain-of-thought reasoning improves accuracy. General-purpose models (GPT-5.5, Claude Sonnet 4.6, Gemini 3.1 Pro) are better for everyday chat, content generation, and tasks where speed and cost matter more than deep reasoning. For agent workflows, consider whether the task requires multi-step planning (use reasoning) or tool-use throughput (use general-purpose). |
| Which model fields matter most for code review selection? | For code review, compare coding capability, reasoning capability, source freshness, SDK support, relationship facts, and related code-review scenario pages. |
| Which models offer the best multilingual support? | Mistral Large 3 offers the strongest multilingual performance among current models, supporting 10+ languages with its 675B MoE architecture. Qwen3.6 provides strong multilingual support with open-weight deployment flexibility. GPT-5.5 and Claude Opus 4.7 also offer broad multilingual capabilities though primarily optimized for English. For production multilingual deployments, evaluate models on your specific language pairs rather than relying on general benchmarks. |
Relationship Facts
| Source | Type | Target | Confidence |
|---|---|---|---|
| claude-opus-4-1 | best_for | agent-workflow | 0.8 |
| claude-opus-4-1 | best_for | code-review | 0.8 |
| claude-opus-4-1 | best_for | reasoning | 0.82 |
Sources
| Name | Type | Citation | Last Verified |
|---|---|---|---|
| Anthropic Claude Models | docs | Official Anthropic model documentation is the primary source for Claude model IDs, context notes, and capability positioning. | 2026-05-21 |
| Anthropic Announcement Blog | official | Official Anthropic announcement blog for Claude Opus 4.7 release details, adaptive thinking, and agent teams features. | 2026-05-21 |
| Anthropic TypeScript SDK | github | GitHub SDK reference for Anthropic server-side TypeScript and JavaScript API usage. | 2026-05-21 |
External Resources
- Anthropic Claude Models — Official Anthropic model documentation is the primary source for Claude model IDs, context notes, and capability positioning.
- Anthropic Announcement Blog — Official Anthropic announcement blog for Claude Opus 4.7 release details, adaptive thinking, and agent teams features.
- Anthropic TypeScript SDK — GitHub SDK reference for Anthropic server-side TypeScript and JavaScript API usage.