SKILL.md
Anthropic Cost Tuning
Overview
Anthropic charges per token. Input tokens, output tokens, and cached tokens each have different prices. Here's how to minimize cost without losing quality.
Pricing (per million tokens)
| Model | Input | Output | Cached Input | Batch Input | Batch Output |
|---|---|---|---|---|---|
| Claude Opus 4 | $15.00 | $75.00 | $1.50 | $7.50 | $37.50 |
| Claude Sonnet 4 | $3.00 | $15.00 | $0.30 | $1.50 | $7.50 |
| Claude Haiku 4.5 | $0.80 | $4.00 | $0.08 | $0.40 | $2.00 |
Cost Reduction Strategies
Instructions
Step 1: Right-Size Your Model
// DON'T use Opus for everything
// DO match model to task complexity:
// Simple classification/extraction → Haiku (cheapest)
const category = await classify(text, 'claude-haiku-4-5-20251001');
// General coding/writing → Sonnet (balanced)
const code = await generate(spec, 'claude-sonnet-4-20250514');
// Complex multi-step reasoning → Opus (best quality)
const analysis = await analyze(data, 'claude-opus-4-20250514');
Step 2: Prompt Caching (90% off input tokens)
// Cache your system prompt — pays for itself after 2 calls
const message = await client.messages.create({
model: 'claude-sonnet-4-20250514',
max_tokens: 1024,
system: [{
type: 'text',
text: longSystemPrompt, // Must be 1024+ tokens
cache_control: { type: 'ephemeral' }, // Cache for 5 minutes
}],
messages,
}, {
headers: { 'claude-beta': 'prompt-caching-2024-07-31' },
});
// First call: cache_creation_input_tokens charged at 1.25x
// Subsequent calls: cache_read_input_tokens charged at 0.1x (90% savings!)
