Pricing pages are where most software trust is won or lost, so let us be plain about how Gravity charges. Gravity is an AI agent platform: you describe an outcome, an expert-built agent runs it, and you get a finished result in about 60 seconds. The pricing matches that simplicity. You pay per use, not per month and not per person, and the only time money moves is when an agent actually runs.

This guide explains the credits model end to end: what a credit is, how usage maps to credits, why pay-per-use suits variable work, and how it differs from a subscription or a per-seat tool. For the broader concept behind this approach, see AI agent pricing explained and the wider survey in AI agent cost models explained.

How Gravity pricing works

Gravity is pay-per-use: $1 buys 1,000 credits, and you are charged only when an agent actually runs and returns a result. There is no subscription, no per-seat fee, and no minimum. You add credits when you want them, an agent spends some each time it does real work, and an account that sits idle costs nothing, per Gravity internal notes, 2026.

That single rule shapes everything else on this page. Because the charge is tied to a completed run, your bill rises and falls with how much work you actually ask for. Run ten tasks in a busy week and you spend more; run nothing the next week and you spend zero. The model is described on the Gravity home page and explained further in agentic AI explained without jargon.

So what does "a run" mean here? A run is one agent completing one task you asked for, start to finish. You describe the outcome, the agent does the work, and the credits for that run are deducted when the result comes back. No result, no charge is the simple promise underneath the whole credits system.

What a credit is and how usage maps to credits

A credit is the unit Gravity uses to measure the work an agent does on a single run, and $1 buys 1,000 credits, per Gravity internal notes, 2026. Credits exist so the price of a run can scale with its real effort rather than a flat fee. A short, simple task draws fewer credits; a longer task that calls several tools draws more, so what you pay maps to what you got.

Why a credit, not a flat per-task price

A flat per-task price would overcharge for trivial work and undercharge for heavy work. Credits avoid that. They let the cost of a quick lookup stay small while a long, multi-step job costs proportionally more. This is the same logic behind metered cloud billing, and it keeps the system honest: you are billed for the effort behind a result, not a rounded-up guess.

What drives the credits a run uses

In our experience, the biggest driver is how much the agent has to do. A run that reads a short prompt and replies once is cheap. A run that pulls data, reasons over it, calls a few tools, and writes a long output costs more, because more underlying compute went into it. The structure behind those steps is covered in AI agent architecture patterns explained.

Why pay-per-use fits real work

Pay-per-use suits variable and low-volume workloads because cost follows usage instead of a calendar. Per Gravity internal notes, 2026, you pay only on a completed run, so months with little work cost little and busy months cost more, without you ever resizing a plan. That alignment is the whole point: you fund results, not the right to maybe use a tool later.

Think about how uneven real work actually is. Some weeks you need an agent five times a day; other weeks, not once. A fixed monthly plan charges you the same through both. Pay-per-use does not. You carry no cost through the quiet stretch and you are never throttled by a plan tier during the busy one.

Especially good for trying things out

This model is forgiving when you are still learning what agents can do for you. You can test an agent on one real task, see exactly what that run cost in credits, and decide whether to keep going, all without committing to a recurring bill. That low-commitment start is part of why pay-per-use shows up among the traits in best AI agent platforms for startups.

How this differs from subscriptions and per-seat tools

The core difference is fixed cost. A subscription charges a flat monthly fee whether you use it heavily or not at all, and a per-seat tool charges for every named user even when some never log in. Gravity has neither. You pay only for completed runs, so there is no monthly floor and no bill for idle seats, per Gravity internal notes, 2026.

The subscription trade-off

Subscriptions can be a fine deal if your usage is high and steady, because a flat fee spread over heavy use gets cheap per task. The trouble starts when usage is uneven. A flat plan keeps charging through your quiet months, and that paid-for-idle gap is exactly what pay-per-use removes. For variable demand, metered usage is usually the kinder fit.

The per-seat trap

Per-seat pricing ties cost to headcount, not to value delivered. Add five people who each run an agent twice a month and you still pay for five full seats. With Gravity there are no seats, so a large team of occasional users costs no more than the work they actually run. If you are weighing tools, the comparison in Gravity vs Zapier shows how this plays out against a per-task automation tool.

How to estimate your spend

Estimating Gravity spend is arithmetic, not guesswork: figure out the credits a typical task uses, multiply by how often you will run it, and convert at $1 per 1,000 credits, per Gravity internal notes, 2026. Because the rate is fixed and you are billed only on real runs, your estimate scales linearly with how much work you actually hand to agents.

A simple way to forecast

Start with one task you care about. Run it a few times, note the credits each run consumed, and take the rough average as your per-task figure. Multiply that by your expected monthly volume, then divide by 1,000 to get dollars. We have found this beats forecasting in the abstract, because real runs reveal the true cost far better than a spreadsheet estimate does.

Start small, then scale

The honest advice is to start small. Add a modest credit balance, run the tasks you genuinely need, and let real usage teach you the numbers before you scale up. Since idle time is free, there is no penalty for ramping slowly. The broader logic of sizing spend to value lives in AI agent cost models explained.

What happens with cheap, expensive, and failed runs

Because credits track the work behind a result, a cheap run and an expensive run are charged differently, and that difference is the whole design. Per Gravity internal notes, 2026, a short task that does little draws fewer credits, while a long task that calls several tools draws more. The credits you spend follow the effort, not a flat sticker.

Cheap runs versus expensive runs

A quick, one-shot answer is the cheap end of the range; it touches little compute, so it costs little. A long job that gathers data, reasons through several steps, and produces a detailed output sits at the expensive end. Neither is good or bad. The point is that you are charged in proportion, so you never overpay for a small task to subsidise a big one.

If a run does not return a useful result

The promise underneath the model is that you pay when an agent runs and returns a result. A run that fails outright and hands back nothing should not feel like money down the drain. If the specifics of a particular failed or partial run are ever unclear, ask Gravity support rather than assume; the platform is built so charges line up with delivered work, and reliability is the subject of the Gravity agent quality bar explained.

Who pays the experts who build the agents

One question new users ask is whether they pay each builder separately. They do not. Gravity pays the experts to build and maintain the agents, and Gravity runs those agents and carries the infrastructure cost, per Gravity internal notes, 2026. Your credits go to Gravity for the run, not to a stack of separate per-builder fees.

This matters for what you actually get. Because builders are paid to maintain their agents over time, the agent you run has been tested and kept current, not shipped once and abandoned. You get a maintained, working agent and a single clear price, which is the arrangement laid out for the people who build them on the for builders page.

Pulling it together, the whole model rests on one idea: charge for delivered work, and nothing else. No subscription, no seats, no per-builder fees, just credits spent on real runs at $1 per 1,000. If you want the plain-language tour of agents themselves, start with the glossary, and the company behind the model is described on the about page.

Frequently asked questions

How does Gravity pricing work?

Gravity pricing is pay per use. You buy credits at a rate of $1 for 1,000 credits, and an agent spends credits only when it actually runs and returns a result. There is no subscription and no per-seat fee, so an account that sits idle costs nothing at all.

What is a Gravity credit?

A credit is the unit Gravity uses to measure the work an agent does on a single run. One dollar buys 1,000 credits. A short, simple task uses fewer credits than a long task that calls several tools, so the credits you spend track the real effort behind each result.

Is Gravity a subscription?

No. Gravity is not a subscription and there is no recurring monthly fee. You add credits when you want them and spend them only when an agent runs. If you do not run anything for a month, you pay nothing for that month, which is the core difference from a flat plan.

Do I pay if I am not using Gravity?

No. You are charged only when an agent runs and hands back a result. Idle time, an open account, and unused seats cost nothing because there are no seats to pay for. Credits you already bought stay in your balance until a run uses them, so a quiet week is free.

How do I estimate my Gravity costs?

Estimate the credits a typical task uses, then multiply by how often you expect to run it. Because $1 equals 1,000 credits, you can convert that figure to dollars directly. Start small, watch what real runs cost, and scale up once you have seen the credits a few live tasks actually consume.

Three things to remember

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