Developers running Claude Code often wonder what the monthly bill will look like before they commit to heavy AI-assisted development. ModelFold, a platform that provides Anthropic-compatible endpoints, answers that question with a cost estimator that breaks down token spend into credits and dollars. The tool is not a subscription quote; it is a pay-per-token model that sits between your code editor and Anthropic's API. A Claude Pro subscription is billed separately by Anthropic and is not included in these numbers.

The estimator works by modeling how many requests a typical development workflow generates in a month. The default preset assumes 1,760 requests spread across 22 days, with each request rounded up and then multiplied by days and requests. That yields 560 credits per day, or $2.80 daily, and 7 credits per individual request. Those are the baseline numbers, but users can adjust the presets to match their actual token counts. Cache reads and reasoning tokens follow the API rules, so the model does not guess those values—it uses whatever the user configures.

Three preset tiers let teams start from a reasonable assumption without building a spreadsheet from scratch. Light assumes 20 days, 30 requests, 12,000 input tokens, and 800 output tokens per request. Regular assumes 22 days, 80 requests, 25,000 input tokens, and 1,500 output tokens. Heavy assumes 22 days, 160 requests, 50,000 input tokens, and 3,000 output tokens. A team that runs fewer queries will fall below Light; a team that prototypes extensively may exceed Heavy. The presets are editable, so the numbers reflect the user's actual context rather than a generic average.

The table below shows the monthly cost for the same usage pattern across different Claude models. Credits convert at 200 credits = $1, and failed generations are not charged. The cheapest model by credit cost is Claude Haiku 5.5 at 1,760 credits ($8.80 monthly). The most expensive is Claude Fable 5 at 56,320 credits ($281.60 monthly). Claude Sonnet 4.5, 4.6, 5, and 5.5 all land at 12,320 credits ($61.60 monthly), while Opus variants range from 21,120 to 28,160 credits depending on the release. These figures let a team compare model expenses before routing traffic to a specific backend.

| Model               | Credits | $     |
|---|---|---|
| Claude Haiku 5.5    | 1,760   | $8.80 |
| Claude Haiku 4.5    | 5,280   | $26.40|
| Claude Sonnet 4.5   | 12,320  | $61.60|
| Claude Sonnet 4.6   | 12,320  | $61.60|
| Claude Sonnet 5     | 12,320  | $61.60|
| Claude Sonnet 5.5   | 12,320  | $61.60|
| Claude Opus 4.5     | 21,120  | $105.60|
| Claude Opus 4.6     | 21,120  | $105.60|
| Claude Opus 4.7     | 21,120  | $105.60|
| Claude Opus 5.5     | 22,880  | $114.40|
| Claude Opus 4.8     | 28,160  | $140.80|
| Claude Opus 5       | 28,160  | $140.80|
| Claude Fable 5      | 56,320  | $281.60|




Paying these prices requires pointing Claude Code at the ModelFold Anthropic-compatible endpoint and supplying a ModelFold API key. The setup guide on the ModelFold site walks through the connection steps. Once configured, the same models are available at the prices listed, so a team can swap endpoints without changing code. Creating an account on ModelFold gives an API key immediately, and the credit system—200 credits for $1—lets a team prepaid budget that scales with actual usage.



For a small team or an individual developer, the estimator reveals that heavy Claude Code use on Sonnet 5 might run about $61.60 per month, while the same workflow on Haiku 5.5 drops to under $9. That spread influences model routing decisions: critical code reviews might use Sonnet, while batch editing or documentation generation could shift to Haiku. The numbers also make it clear that failing a generation carries no cost, so teams can experiment freely without worrying about charged empty returns.



Why this matters for teams: knowing the monthly cost up front prevents surprise bills when developers integrate AI deeply into their workflow. The estimator turns abstract "token spend" into concrete dollars, and the preset tiers mean a team can start with a reasonable guess and refine it after a few days of actual usage. The ModelFold endpoint also means the cost model travels with the configuration—no need to rewrite prompts or change tooling when moving between environments.



A natural ending: any team evaluating AI-assisted development should run the estimator with their actual request patterns before committing to a model tier. The numbers are transparent, the presets are editable, and the pay-per-token model means you only pay for what your code actually triggers.