Rocket.new Pricing 2026, Plans, Tokens, and Real Costs

Rocket.new pricing is token metered. You subscribe to a monthly plan that buys a pool of tokens, and every prompt, edit, retry, and regeneration draws from that pool. Two teams on the same tier can pay very different amounts for the same feature.

Plan tables are the easy part of Rocket.new pricing. The number that decides your budget is cost per feature that survives code review, and no vendor prints that on a pricing page.

You have probably opened three comparison posts already, found three different sets of numbers, and closed all of them no wiser. Token allowances and tier prices in this category get revised often, and most third party tables go stale within a quarter. So this post takes a different route. It explains how token billing drains a budget, gives you a repeatable way to calculate your own cost, and shows where a backend heavy project quietly doubles the bill.

Key Takeaways

How Rocket.new pricing works in 2026

Rocket.new sells a subscription that includes a monthly token allowance. Tokens are the metering unit, and they are consumed by the work the model does on your behalf rather than by the number of people on your team.

Three things move the meter on every request.

• Input context. The size of your prompt plus whatever the builder pulls in from your existing project.

• Output size. A full CRUD module with views costs more than a single controller method.

• Model choice. Higher capability models burn the allowance faster per request.

That structure has one honest advantage. A solo developer who prompts carefully can run a whole side project inside a modest plan, because nobody pays for a seat they barely use. It also has a hard edge. Spend becomes unpredictable exactly when you are moving fastest, since one stubborn feature can eat a week of allowance in an afternoon.

Curious how the same build looks when the backend is the point rather than the afterthought? Try StackMivo Now.

Before you budget anything, open Rocket.new's official site and read the current plan page yourself. Search demand splits between Rocket.new pricing and the dot free variants people actually type, rocket new pricing and rocket new plans, but the question behind all of them is identical. What does one shipped feature cost?

What Rocket.new plans include and what to verify first

The tier structure follows the pattern most prompt based builders use. A free tier for evaluation with a small token allowance, an individual paid tier, a pro or team tier with more tokens and collaborators, and a business or enterprise arrangement with custom limits. Annual billing normally carries a discount over monthly.

That shape is stable. The numbers inside it are not, which is why a checklist beats a memorised price.

1. Monthly token allowance and reset date. Confirm whether unused tokens roll over or expire at the end of the cycle.

2. Top up cost. Find the price of an extra token pack, because heavy months will need one.

3. Seats included. Check what a second or third collaborator adds to the monthly total.

4. Private projects. Verify which tier is the first to keep your work out of public view.

5. Code export and ownership. Confirm you can pull the full source out and keep running it without the platform.

6. Hosting and deployment. Ask what is bundled and what you pay a separate provider for.

7. Model selection. See whether you control which model runs, since that sets your burn rate directly.

Items five and six catch teams out most often. A cheap build is expensive if you cannot take the result with you, and the same trap shows up across the whole category, which is why the comparison of how prompt based builders handle backend work keeps returning to ownership rather than raw output speed.

The three costs Rocket.new pricing does not show you

The retry tax

Every failed generation is billed. Nothing refunds a prompt that produced the wrong shape, so the accurate unit of cost is tokens per accepted result, not tokens per request.

A two person team building a booking MVP learned this in their second week. The simple screens landed on the first prompt. The availability logic, overlapping reservations, timezone handling, and a cancellation window, took 11 prompts across two afternoons before the generated version matched the rules their client had actually agreed. Same plan, same month, and that one feature consumed more allowance than the previous 14 combined. Nothing was broken. They had simply budgeted as though every prompt lands first time.

The backend rework tax

Generated frontends are usually close enough to keep. Backends are where hand written hours reappear, and hours cost more than tokens.

The recurring gaps are specific. Multi role authorization that needs real policy classes, background jobs that need a queue and a worker, relational integrity across five or six tables, and an API layer that stays stable while the schema moves. Laravel has first party answers for all of it, and the Laravel authorization documentation is a fair yardstick. If a generated app produces nothing resembling that structure, a developer writes it later at full rate. That gap is the whole subject of the comparison of which AI builders generate real backends.

The seat and handoff tax

Token pricing looks cheap for one person and stops looking cheap the moment a build becomes a team effort. Two developers prompting the same project duplicate context, duplicate retries, and duplicate spend. Add a review step and somebody pays twice for the same feature.

Here is where the money actually goes.

How to calculate your real Rocket.new cost per shipped feature

Do this before you commit a quarter of budget. It takes one afternoon on a free tier, and it is the only number that transfers to your own project.

1. Pick a representative feature. Not a landing page. Choose something with rules, like role based access or a recurring booking.

2. Build it end to end and count every prompt. Include the retries, the corrections, and the abandoned attempts.

3. Record tokens consumed for one accepted result. That is your true unit cost.

4. Add the hand finishing hours. Time what you rewrite yourself, then price it at your real rate.

5. Divide the plan price by that unit. You now know how many real features a tier buys per month.

Most teams find the hand finishing line dwarfs the token line. An agency lead who ran this exercise across three prompt based tools reported the same pattern each time. Token spend stayed affordable and roughly predictable. What broke the estimate was the queue configuration, the notification jobs, and the permission matrix, all rewritten by a senior developer at senior rates. Laravel's queue documentation shows how much structure that work involves once you move past a single job.

Generation quality is therefore a pricing feature, not a bonus. AI code generation that produces the right structure on the first attempt lowers the retry count and the rework count together.

Rocket.new pricing compared with a Laravel native credit model

Credit models answer the predictability problem differently. A credit maps to a unit of work rather than to the model's token consumption, so the monthly total is easier to forecast even when a feature fights back.

StackMivo pricing is published in full. Free includes 10 credits, 2 projects, and 1 seat. Starter is $29 a month billed annually with 150 credits, unlimited projects, 2 seats, and private projects. Pro is $79 a month billed annually with 350 credits and 5 seats. Agency is $199 a month billed annually with 1,800 credits and 10 seats. Yearly billing saves 20%.

The output difference matters more than the price difference. StackMivo generates production-ready Laravel apps, meaning Eloquent models and relationships, migrations, controllers, Policies, FormRequests, API Resources, Filament admin resources, and Pest tests, as standard Laravel code you own and keep. Supported versions run from Laravel 9 through 12, and shipping uses one-click deployment to Laravel Cloud, Forge, Ploi, or an SSH server, with migrations run automatically.

Be fair about the trade off. If your product is a React interface and there is no Laravel anywhere in your stack, a Laravel native builder is the wrong tool at any price. Rocket.new pricing is competitive for exactly that kind of work.

When Rocket.new is worth the spend and when it is not

Pick Rocket.new when the interface is the product. Prototypes, marketing sites, internal dashboards with light logic, and anything you want in front of users this week suit token metered pricing well, because those builds land in few prompts and rarely need a rewritten backend.

Choose differently when the backend is the product.

• Multi tenant SaaS with per tenant data isolation and role based permissions.

• Anything with billing, webhooks, and retry logic that has to be correct.

• Systems with queues, scheduled work, and notification pipelines.

• An existing Laravel codebase that new features must fit into rather than replace.

That last case is the expensive one. Rewriting a working Laravel application to suit a builder's preferred stack costs more than every subscription in this comparison combined, which is why multi tenant SaaS builds belong on a Laravel native path from the very first prompt.

You can generate a production-ready Laravel app from a plain English description and own every line of the result. Get started free.

The bottom line on Rocket.new pricing

Rocket.new pricing is easy to read and hard to predict, because tokens bill for effort rather than for outcomes. The tier you pick matters less than the retry rate on your hardest feature and the hours you spend finishing what the model started.

Four things to carry away. Verify the current allowance and top up price at the source, since third party tables go stale fast. Measure your own cost per accepted feature on a free tier before you commit real budget. Price the hand finishing work, because on backend heavy projects it usually exceeds the subscription. And treat code ownership as a cost line, since a build you cannot export is a build you pay for twice.

Run that afternoon experiment on every tool on your shortlist. One representative feature, honestly counted, tells you more than any pricing page ever will. Then back the tool whose output your team would have written anyway, and keep the difference.