Cost Optimization Intermediate

Understanding how Claude Code costs work and applying smart optimization strategies can reduce your spending by 50% or more without sacrificing quality. Learn token economics, model selection, and budget management.

Token Usage Breakdown

Every Claude Code interaction involves two types of tokens:

Token Type What It Includes Cost Impact
Input tokens Your prompt, CLAUDE.md, file contents read, command outputs, conversation history Lower cost per token
Output tokens Claude's responses, code it generates, explanations Higher cost per token (3-5x input)
Key Insight: Input tokens grow with every turn of conversation because the entire history is sent with each request. A 20-turn conversation sends the full history 20 times. This is why /compact saves so much money.

Model Selection Impact

Model Best For Relative Cost Quality
Claude Sonnet Routine tasks, simple fixes, code generation $ Very Good
Claude Opus Complex reasoning, architecture, tricky bugs $$$$ Excellent
Terminal
# Use Sonnet for routine tasks (default)
$ claude -p "Add input validation to the signup form"

# Switch to Opus for complex tasks
$ claude -p "Redesign the caching layer to support Redis Cluster" --model claude-opus-4-20250514

# In interactive mode, switch models mid-session
> /model claude-opus-4-20250514

Cost-Saving Strategies

1. Use /compact Regularly

The /compact command summarizes the conversation, dramatically reducing input tokens for subsequent turns:

Example
# After 10 turns of conversation (~50K tokens accumulated)
> /compact

# Conversation is summarized to ~5K tokens
# Next 10 turns cost 90% less in input tokens!

2. Write Shorter, More Specific Prompts

Comparison
# Expensive: vague prompt causes Claude to search and read many files
> I think there's a bug somewhere in the auth system, can you find it?

# Cheap: direct prompt, Claude goes straight to the fix
> Fix the null check on line 45 of src/auth/session.ts - it should check for undefined too

3. Use -p for Quick Tasks

One-shot mode has zero conversation overhead - no history accumulation:

Terminal
# Each call is independent - no growing context
$ claude -p "Fix the typo on line 12 of README.md"
$ claude -p "Add a .gitignore entry for .env.local"
$ claude -p "Remove the unused import on line 3 of src/app.ts"

4. Leverage Caching

Claude Code benefits from prompt caching when conversation prefixes are reused. This happens automatically - your CLAUDE.md content and early conversation history are cached across turns.

5. Monitor with /cost

Terminal
# Check current session cost
> /cost

# Output example:
# Session cost: $0.47
# Input tokens: 125,430
# Output tokens: 8,210
# Cache hits: 89,200 tokens (saved ~$0.25)

Cost Comparison: Task Types

Task Estimated Cost Optimization
Quick fix (1 file, -p) $0.01 - $0.05 Already optimal
Feature implementation (5-10 files) $0.20 - $1.00 Use specific file paths, Sonnet model
Large refactoring (20+ files) $1.00 - $5.00 /compact regularly, break into sessions
Full codebase review $2.00 - $10.00 Review in sections, use Sonnet
Architecture planning $0.50 - $3.00 Use Opus only for the planning phase

Monthly Cost Estimation

Usage Pattern Estimated Monthly Cost
Light (5-10 quick tasks/day) $10 - $30
Moderate (20+ tasks/day, mixed complexity) $50 - $150
Heavy (all-day usage, complex projects) $150 - $500
Team (5 developers, moderate usage) $250 - $750
Rule of Thumb: Use Sonnet for 80% of tasks and Opus for the remaining 20% that truly need it. This alone can cut costs by 40-60% compared to using Opus for everything.

Setting Budget Alerts

Set up monitoring to prevent unexpected costs:

  • Check the Anthropic Console for usage dashboards and spending limits
  • Set monthly spending limits on your API key
  • Use /cost at the end of each session to track trends
  • Create a simple tracking script that logs daily costs

Try It Yourself

Check your current session cost with /cost and try using /compact to see the impact. Try using Sonnet for your next few routine tasks. Next: mastering CLAUDE.md files.

Next: CLAUDE.md Mastery →

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