Claude Code's 1M Context Window Is Now GA — And It's Priced Like Regular Context

Claude Opus 4.6 and Sonnet 4.6 now support 1M tokens with no long-context premium, making massive codebase analysis cheaper than competitors.

3d ago·4 min read·5 views·via simon_willison
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Claude Code's 1M Context Window Is Now GA — And It's Priced Like Regular Context

What Changed

As of March 2026, Anthropic has made the 1 million token context window generally available for both Claude Opus 4.6 and Sonnet 4.6. This isn't just a capacity increase—it's a pricing breakthrough. Unlike OpenAI and Google, which charge premium rates for extended context, Anthropic applies standard pricing across the entire 1M window.

Specifically:

  • Gemini 3.1 Pro charges more above 200,000 tokens
  • GPT-5.4 charges more above 272,000 tokens
  • Claude 4.6 models charge the same rate from 1 token to 1,000,000 tokens

What This Means For Claude Code Users

For developers using Claude Code daily, this changes how you should approach large-scale code analysis and refactoring. Previously, you might have hesitated to load your entire monorepo into context due to cost concerns. Now, you can analyze complete codebases in a single session without worrying about hitting a premium pricing tier.

Consider these practical implications:

  1. Full repository analysis becomes economically viable
  2. Multi-file refactoring across dozens of files can happen in one conversation
  3. Documentation generation from your entire codebase is now a single prompt
  4. Architecture reviews that previously required chunking can be done holistically

How To Use It Right Now

1. Load Your Entire Project

Instead of working file-by-file, you can now load your entire project structure:

claude code --context-size 1000000 analyze-project /path/to/your/project

2. Create Comprehensive CLAUDE.md Files

Your CLAUDE.md can now reference your entire codebase. Instead of just local patterns, document global architecture:

# Project Architecture

## Core Systems (see /src/core/)
- Authentication: Uses JWT with refresh token rotation
- Database: PostgreSQL with connection pooling
- Caching: Redis cluster for session storage

## API Structure (see /src/api/)
- REST endpoints follow OpenAPI 3.0 spec
- GraphQL layer for internal services
- WebSocket support for real-time features

## Testing Strategy (see /tests/)
- Unit tests: Jest with 90% coverage requirement
- Integration: Cypress for E2E flows
- Performance: Load testing with k6

3. Batch Refactoring Operations

Instead of refactoring one component at a time, you can now describe system-wide changes:

"Refactor all API endpoints to use the new error handling middleware. Update:
1. All controllers in /src/api/controllers/
2. The middleware in /src/middleware/errorHandler.js
3. Test files in /tests/api/
4. Documentation in /docs/api/

Ensure backward compatibility and update all TypeScript interfaces."

4. Cross-Repository Analysis

If you work with microservices, you can now analyze multiple related repositories:

# Create a combined context from multiple repos
claude code --context-size 1000000 \
  --include /path/to/auth-service \
  --include /path/to/user-service \
  --include /path/to/api-gateway \
  analyze-dependencies

The Competitive Advantage

While other AI coding assistants charge premiums for long context, Claude Code gives you 1M tokens at standard rates. This means:

  • Cost predictability: No surprise charges when your analysis grows
  • Better reasoning: Claude can maintain context across your entire codebase
  • Fewer context switches: Complete understanding leads to better suggestions

Practical Limitations to Consider

Even with 1M tokens, you still need to be strategic:

  1. Token efficiency matters: Use --compact flag to reduce whitespace
  2. Focus on relevant files: Don't load node_modules or build artifacts
  3. Use .claudeignore: Create ignore patterns for generated files
  4. Prioritize active development areas: Load recent changes first

Next Steps

Update your Claude Code installation to ensure you're using Opus 4.6 or Sonnet 4.6, then experiment with loading larger portions of your codebase. Start with a medium-sized project (50-100 files) and work your way up to your largest codebases.

The era of piecemeal AI assistance is over. With 1M context at standard pricing, you can finally treat Claude Code as a true partner who understands your entire system.

AI Analysis

Claude Code users should immediately change their workflow to take advantage of the 1M context window. Instead of working file-by-file, start loading entire directories or projects. Use `claude code --context-size 1000000` as your default for complex tasks. Create more comprehensive CLAUDE.md files that document your entire architecture, not just local patterns. Reference multiple directories and cross-file relationships. When refactoring, describe system-wide changes in a single prompt rather than iterating through components. For cost-sensitive projects, this is particularly impactful. You can now analyze complete codebases without hitting premium pricing tiers that competitors charge. Use this for architecture reviews, documentation generation, and large-scale refactoring that previously required manual chunking.
Original sourcesimonwillison.net

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