Model comparison
Haiku 5.5 vs Sonnet 5.5: Workload Cost Comparison
Haiku 5.5 and Sonnet 5.5 have different token prices, but the budget depends on prompt length, output volume, caching, and how many attempts produce an acceptable result. Compare a workload before choosing a model.
Use the same billing scope
This comparison uses direct Claude API standard token prices from our shared pricing table. It excludes subscriptions, Batch, regional uplifts, tools, and negotiated discounts. The examples are calculations, not measured performance benchmarks.
Haiku 5.5 has a separate price tier when a request's input exceeds 100,000 tokens. The threshold applies to each request, not the sum of a month of traffic. The long-input example below uses the higher tier for both input and output.
Four workloads, one calculation method
Each row represents 1,000 requests. Short input uses 10,000 input and 1,000 output tokens per request. Output-heavy work keeps the input at 10,000 but raises output to 10,000. Long input uses 120,000 input and 2,000 output tokens.
The cache-reuse scenario uses 10,000 input and 1,000 output tokens per request, with 80% of input read from cache, 10% written at the five-minute rate, and 10% uncached. These are assumed token shares, not a measured hit rate. Prices and totals below are generated from the same data and decimal arithmetic as the calculator.
| Workload | Haiku 5.5 | Sonnet 5.5 |
|---|---|---|
| Short input | $1.50 | $30.00 |
| Output-heavy | $6.00 | $120.00 |
| Long input (>100K) | $65.00 | $260.00 |
| Cache reuse | $0.81 | $15.30 |
Understand what changes the gap
Longer output increases the part of the bill charged at the output rate. Cache reuse reduces only the eligible input component, while cache writes still have a cost. Changing one of these assumptions can change the absolute saving even when the model names stay the same.
Do not apply the short-input Haiku price to a long request or treat repeated text as a guaranteed cache hit. Tokenizers, request formatting, cache eligibility, and actual output length can all change a real workload. Use returned usage fields to replace the assumptions after a pilot.
Compare cost per accepted result
Equal token counts make a clean price comparison, but do not establish equal quality. Start with a small set of real tasks and a written acceptance rule: valid output format, correct answer, passing tests, or a human review criterion.
Measure the cost of all attempts divided by the number of accepted results. Include retries, review time, and escalation to another model. A cheaper first attempt may still be a good choice, but the saving should survive the entire workflow.
- Use the same task set and acceptance criteria for both models.
- Record output quality, latency, token counts, and retries separately.
- Test a routing rule on held-out tasks before scaling it.
- Keep an escalation path for tasks that fail the first model's checks.
Turn the comparison into an operating budget
Use the calculator to enter your own request volume and cache shares. Split short and long inputs into separate groups. Keep the price check date with the budget, especially when a rollout spans several billing periods.
After launch, reconcile against the provider's reported API costs. Quota Monitor's Anthropic connection can track supported organization or workspace cost and limit information; it does not attribute every local Claude Code task or read subscription allowance. The setup guide explains the exact scope and verification status.
Common questions
- Does the cheaper token price make Haiku the right choice for every task?
- No. This page compares billing scenarios, not task quality. Evaluate the cost per accepted result, including retries and escalation, for your own workload.
- Does one million tokens per month trigger the Haiku long-input tier?
- No. The tier depends on the input of an individual request. Many short requests remain in the short-input tier even when their combined volume is large.