Originally published at claudeguide.io/claude-api-cost-optimization-guide

Claude API Cost Optimization: Complete Guide to Reducing Your Bill

Claude API costs can be reduced by 60–90% through a combination of four techniques: model routing (use Haiku for 40–60% of requests), prompt caching (eliminate repeated system prompt costs), batch processing (50% discount for non-real-time work), and token efficiency (reduce input size). Each technique is independent — implement them in order of impact for your specific usage pattern, starting with model routing.

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Your cost breakdown (start here)

Before optimising, understand where your costs come from. Most applications have costs concentrated in a few places:

python
import anthropic
from collections import defaultdict

client = anthropic.Anthropic()
cost_tracker = defaultdict(lambda: {"input": 0, "output": 0, "requests": 0})

def tracked_create(request_type: str, **kwargs) -

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