Claude Opus 4.6 vs Opus 4.5: What 1M Context Means for Devs
A practical comparison of Claude Opus 4.6 and 4.5 for coding: context window, quality, and when to use each model.
Editorial Team
The AI Coding Tools Directory editorial team researches and reviews AI-powered development tools to help developers find the best solutions for their workflows.
Claude Opus 4.6 introduces a 1M token context window and coding improvements. This guide compares it to Opus 4.5 for developers.
Quick Answer
Opus 4.6 adds 1M context (vs 200K in 4.5) and refinements for coding. Use 4.6 for large codebases, multi-file refactors, and long docs. 4.5 remains strong for typical tasks and may be cheaper. Availability depends on your tool (Cursor, Claude Code, API, etc.).
Key Differences
| Aspect | Opus 4.5 | Opus 4.6 |
|---|---|---|
| Context window | 200K tokens | 1M tokens |
| Coding quality | Excellent | Improved |
| Long-context retention | Good | Better |
| Cost | Lower input cost | Higher for long context |
| Availability | Widely available | Rolling out by product |
When 4.6 Matters
| Task | Why 4.6 helps |
|---|---|
| Large codebase navigation | More files in context at once |
| Multi-file refactors | See dependencies without chunking |
| Long documentation | Keep full docs in context |
| Cross-repo analysis | Pull in multiple repos if supported |
When 4.5 Is Enough
| Task | Why 4.5 suffices |
|---|---|
| Single-file edits | 200K is plenty |
| Short conversations | No need for 1M |
| Cost sensitivity | 4.5 may be cheaper per request |
| Quick completions | Speed may matter more than context |
Where to Use Each
- Claude Code: Check which Opus version is default; switch if needed.
- Cursor: Pro+ and Ultra typically offer latest Claude models; verify in model picker.
- Claude API: Both 4.5 and 4.6 available; choose by context needs.
- Windsurf, Copilot: Model availability varies; see each tool's docs.
Practical Takeaway
For most coding tasks, 4.5 is still excellent. Upgrade to 4.6 when you routinely hit context limits or work with very large codebases. Compare pricing if you are cost-sensitive. See Claude Code and Cursor for integration details.
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Tools Mentioned in This Article
Claude Code
Anthropic's terminal-based AI coding agent with 80.9% SWE-bench, Agent Teams, and GitHub Actions
SubscriptionClaude Opus 4.6
Anthropic's frontier reasoning model: 80.9% SWE-bench record, 1M token beta context, and adaptive thinking
Pay-per-useCursor
The AI-native code editor with $1B+ ARR, 25+ models, and background agents on dedicated VMs
FreemiumWindsurf
AI-native IDE with Cascade agents and SWE model family
PaidWorkflow Resources
Cookbook
AI-Powered Code Review & Quality
Automate code review and enforce quality standards using AI-powered tools and agentic workflows.
Cookbook
Building AI-Powered Applications
Build applications powered by LLMs, RAG, and AI agents using Claude Code, Cursor, and modern AI frameworks.
Cookbook
Building APIs & Backends with AI Agents
Design and build robust APIs and backend services with AI coding agents, from REST to GraphQL.
Cookbook
Debugging with AI Agents
Systematically debug complex issues using AI coding agents with structured workflows and MCP integrations.
Skill
Change risk triage
A systematic method for categorizing AI-generated code changes by blast radius and required verification depth, preventing high-risk changes from shipping without adequate review.
Skill
Configuring MCP servers
A cross-tool guide to setting up Model Context Protocol servers in Cursor, Claude Code, Codex, and VS Code, including server types, authentication, and common patterns.
Skill
Local model quality loop
Improve code output quality when using local AI models by combining rules files, iterative retries with error feedback, and test-backed validation gates.
Skill
Plan-implement-verify loop
A structured execution pattern for safe AI-assisted coding changes that prevents scope creep and ensures every edit is backed by test evidence.
MCP Server
AWS MCP Server
Open source MCP servers from AWS Labs that give AI coding agents access to AWS documentation, best practices, and contextual guidance for building on AWS.
MCP Server
Docker MCP Server
Docker MCP Gateway orchestrates MCP servers in isolated containers, providing secure discovery and execution of Model Context Protocol servers across AI coding tools.
MCP Server
Figma MCP Server
Official Figma MCP server that brings design context, variables, components, and Code Connect data into AI coding sessions for design-to-code workflows.
MCP Server
Firebase MCP Server
Experimental Firebase MCP server that gives AI coding agents access to Firestore, Auth, security rules, Cloud Messaging, and project management through the Firebase CLI.
Frequently Asked Questions
What is new in Claude Opus 4.6?
Is Claude Opus 4.6 better for coding than 4.5?
Where can I use Claude Opus 4.6?
Does 1M context cost more?
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