Anthropic Cost Tuning

Overview

Optimize Claude API spend through model routing, prompt caching, the Message Batches API, and real-time cost tracking. The four biggest levers: model selection (4-19x), prompt caching (10x input), batches (2x), and max_tokens discipline.

Pricing Reference (per million tokens)

Model	Input	Output	Cache Read	Cache Write
Claude Haiku	$0.80	$4.00	$0.08	$1.00
Claude Sonnet	$3.00	$15.00	$0.30	$3.75
Claude Opus	$15.00	$75.00	$1.50	$18.75

Message Batches: 50% off all model pricing for async processing.

Cost Calculator

def estimate_cost(
    input_tokens: int,
    output_tokens: int,
    model: str = "claude-sonnet-4-20250514",
    cached_input: int = 0,
    use_batch: bool = False
) -> float:
    pricing = {
        "claude-haiku-4-20250514": {"input": 0.80, "output": 4.00, "cache_read": 0.08},
        "claude-sonnet-4-20250514": {"input": 3.00, "output": 15.00, "cache_read": 0.30},
        "claude-opus-4-20250514": {"input": 15.00, "output": 75.00, "cache_read": 1.50},
    }
    rates = pricing[model]
    uncached_input = input_tokens - cached_input

    cost = (
        uncached_input * rates["input"] +
        cached_input * rates["cache_read"] +
        output_tokens * rates["output"]
    ) / 1_000_000

    if use_batch:
        cost *= 0.5

    return cost

# Example: 10K requests/day, 500 input + 200 output tokens each
daily = estimate_cost(500, 200, "claude-sonnet-4-20250514") * 10_000
print(f"Daily: ${daily:.2f}")      # ~$0.045 * 10K = $450/day
print(f"Monthly: ${daily * 30:.2f}")  # ~$13,500/month

# Same with Haiku + batching
daily_optimized = estimate_cost(500, 200, "claude-haiku-4-20250514", use_batch=True) * 10_000
print(f"Optimized: ${daily_optimized:.2f}/day")  # ~$22/day (20x cheaper)