Calculate Your Cost
Tier rule used here: total prompt tokens = fresh input + cache writes + cache reads. Anthropic has not clarified whether cached tokens count toward the 100K line, so this calculator budgets as if they do.
Your Estimate
Standard tier
Cost per request: $0.00
Estimated monthly cost: $0.00
Claude Haiku 5.5 Rate Card (per 1M tokens)
| Token type | Haiku 5.5 ≤100K | Haiku 5.5 >100K | Haiku 4.5 | Sonnet 5.5 |
|---|---|---|---|---|
| Input | $0.10 | $0.50 | $1.00 | $2.00 |
| Output | $0.50 | $2.50 | $5.00 | $10.00 |
| Cache write, 5 min | $0.125 | $0.625 | $1.25 | $2.50 |
| Cache write, 1 hour | $0.20 | $1.00 | $2.00 | $4.00 |
| Cache read | $0.01 | $0.05 | $0.10 | $0.10 |
| Batch input | $0.05 | $0.25 | $0.50 | $1.00 |
| Batch output | $0.25 | $1.25 | $2.50 | $5.00 |
Rates from Anthropic's official Haiku 5.5 launch post and pricing page, verified October 20, 2026. Haiku 5.5: 1M-token context window, up to 128K output tokens per request, model ID claude-haiku-5-5.
The 100K Cliff: What Actually Drives Your Bill
- The tier is chosen per request, and it re-prices everything. A 100,001-token prompt does not just pay more for the extra token — input, cache and output for that whole request bill at 5× the base rates.
- Output price follows the prompt's tier. The length of what you send decides the price of what comes back: the same 1,000-token answer costs $0.0005 under the line and $0.0025 over it.
- Budget cached tokens as counting toward the line. Anthropic has not clarified this either way. A giant cached system prompt may save on reads and still push the request into the 5× tier — keep total prompt size in view, not just fresh input.
- Recount your tokens. Haiku 5.5's new tokenizer produces roughly 30% more tokens for the same text than Haiku 4.5's. Every estimate, limit and budget carried over from 4.5 is stale.
- Stay under the line by compacting, not by hoping. Trim conversation history, summarize tool output, and move static context into cache — then check the total prompt size in this calculator before you ship.
- Stack the boring discounts. Batch API halves input and output for anything that can wait up to 24 hours, and cache reads cost a tenth of fresh input on short prompts. Combined, routine workloads run at a small fraction of list price.
FAQ
How much does Claude Haiku 5.5 cost?
Two tiers, set by prompt length: up to 100,000 prompt tokens, $0.10 per million input and $0.50 per million output; over 100,000, the whole request bills at $0.50 / $2.50. Cache reads are $0.01 or $0.05 per million by tier.
What is the 100K-token price cliff?
Haiku 5.5 picks a price tier per request from the total prompt size. Cross 100K tokens and every token in that request — input, cache and output — bills at the 5× long-context rates. It is a cliff, not a marginal bracket.
Do cached tokens count toward the 100K threshold?
Anthropic has not publicly clarified this. This calculator counts all prompt tokens (fresh input + cache writes + cache reads) toward the threshold, so the estimate errs on the safe side.
How does the Batch API discount work?
Batch requests run asynchronously, typically within 24 hours, at 50% off input and output tokens: $0.05 / $0.25 per million under 100K, $0.25 / $1.25 over it. Cache pricing applies as usual.
Why does the same text use more tokens than on Haiku 4.5?
Haiku 5.5 uses a new tokenizer that produces approximately 30% more tokens for the same text. Recount prompts before rebudgeting, and re-check your max_tokens limits.
How much cheaper is Haiku 5.5 than Haiku 4.5?
90% cheaper on short prompts, 50% cheaper on long ones. Anthropic's blended estimate for real workloads is about 75% average savings after request mix and the tokenizer change.
Methodology & sources: rates verified against Anthropic's official launch post and pricing page on October 20, 2026 (anthropic.com/claude-haiku-5-5). Estimates exclude server-side tool fees (e.g. web search at $10 per 1,000 calls), the 1.1× US-only inference multiplier, and taxes. This is an estimate, not a quote — your invoice follows Anthropic's metered usage.
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