Prompt Cache ROI Calculator
Prompt Cache ROI Calculator
Project monthly savings and breakeven from prompt caching across Anthropic and OpenAI models with embedded May 2026 pricing.
Prompt structure
Fraction of calls landing on a warm cache. 100% = always warm; 0% = every call writes fresh.
Selected model
Cache read 90% off input; first-write surcharge 25%.
| Model | No-cache / mo | Cached / mo | Savings | Savings % | Breakeven |
|---|---|---|---|---|---|
Claude Opus 4.7 Anthropic | $11250 | $6012 | $5238 | 46.6% | 1 calls |
Claude Sonnet 4.6 Anthropic | $2250 | $1202 | $1048 | 46.6% | 1 calls |
Claude Haiku 4.5 Anthropic | $750 | $401 | $349 | 46.6% | 1 calls |
GPT-4o OpenAI | $1755 | $1245 | $510 | 29.1% | — |
GPT-4o Mini OpenAI | $105 | $74.70 | $30.60 | 29.1% | — |
Without caching, every call pays the full input rate on (static + query) tokens. With caching, the first call writes the static prefix at the cache-write rate (Anthropic adds a 25% surcharge on writes; OpenAI does not), and every subsequent warm read replaces input rate with the cached-read rate (90% off Anthropic, 50% off OpenAI). Hit rate scales how many of your monthly calls land on a warm prefix.
What This Tool Does
Prompt Cache ROI Calculator is built for deterministic developer and agent workflows.
Compute Anthropic and OpenAI prompt-caching breakeven and projected monthly savings vs no-cache, with embedded May 2026 pricing for Claude and GPT models.
Use How to Use for execution steps and FAQ for constraints, policies, and edge cases.
Last updated:
This tool is provided as-is for convenience. Output should be verified before use in any production or critical context.
Agent Invocation
Best Path For Builders
Browser workflow
Runs instantly in the browser with private local processing and copy/export-ready output.
Browser Workflow
This tool is optimized for instant in-browser execution with local data handling. Run it here and copy/export the output directly.
/prompt-cache-roi-calculator/
For automation planning, fetch the canonical contract at /api/tool/prompt-cache-roi-calculator.json.
How to Use Prompt Cache ROI Calculator
- 1
Describe your prompt structure
Enter the static prefix size (system, few-shot, retrieved context that stays constant), per-call query tokens, average output tokens, and how many calls per day you expect. Each field accepts plain integers.
- 2
Set the cache hit rate
The slider controls what fraction of monthly calls land on a warm prefix. Real-world hit rates depend on TTL and traffic shape — try 80-95% for steady traffic and lower values for spiky workloads.
- 3
Pick a model
Each model card shows input, cached read, cache write (Anthropic only), and output prices per million tokens. The May 2026 figures cover Claude Opus 4.7, Sonnet 4.6, Haiku 4.5, GPT-4o, and GPT-4o-mini.
- 4
Read savings and breakeven
Headline tiles show no-cache vs cached monthly cost, dollar savings, and how many warm reads pay back the first cache write. The full comparison table runs the same calculation across every embedded model.