Hostinger GPU instances use prepaid account credits, not a fixed monthly subscription. Billing begins as soon as you deploy an instance and continues at the displayed hourly burn rate while that GPU resource exists, even when it is idle. To control spending, open Dev tools → GPU, inspect Current credits and the credits-per-hour rate, top up before a long job, and destroy the instance when the workload ends.
Do not rely on rebooting, an automatic low-balance warning, or a grace period. Hostinger says an instance can be destroyed immediately when the shared credit balance reaches zero, and GPU instances do not include automated backups or persistent storage. Copy anything important elsewhere before you run out of credits or terminate the resource.
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How Hostinger GPU billing works
Hostinger GPU is a prepaid system. You add credits to your Hostinger account, deploy a GPU instance, and spend those credits as the allocated resource runs. Hostinger’s Help Center states that “Billing starts immediately when you deploy a Hostinger GPU instance.” The hourly charge continues for as long as the GPU resource remains allocated to your account.
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That last point is the one that most often causes an unexpectedly large bill: an idle instance still consumes credits. A training script that has finished, an inference server waiting for requests, or a terminal session left open does not release the GPU. The Hostinger Hosting Agreement describes the rule this way: “Charges accrue for as long as the relevant GPU resource remains allocated to you, including when you are not actively running a workload, and continue until you terminate or release the resource.”
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Rebooting the machine does not end the allocation. The billing article does not describe a pause or stop mode that preserves the instance configuration while suspending charges, so treat destroy or terminate as the action that ends GPU billing.
What determines the hourly cost
The rate depends on the GPU, instance size, and region you select. Hostinger has not published a complete, stable hourly-rate table in the billing documentation covered here. Use the price and credits-per-hour figure shown on the deployment screen and GPU overview as the authoritative value for the exact configuration you are about to run. Do not apply a rate from a different GPU model, size, or location.
Hostinger’s GPU setup documentation says that one euro is roughly equal to 100 credits. That is an approximate conversion, not a promise that every payment, promotion, tax treatment, or regional price will follow the same ratio. Your account balance and the deployment screen remain the practical sources for planning.
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The information needed to manage a running instance is in the Hostinger control panel. Use this path every time you start a paid workload:
- Sign in to Hostinger.
- Open Dev tools in the side panel.
- Select GPU.
- Choose Manage for the relevant instance.
- Read the overview’s Current credits, running-instance information, spending details, and credits-per-hour burn rate.
The burn rate lets you turn a balance into a rough runtime estimate. Divide the credits currently available by the displayed credits-per-hour figure. The result is an estimate only: it assumes the rate remains unchanged and that no other service draws from the same shared balance. Check the overview again immediately before a long training run, rendering queue, batch job, or unattended inference service.
Why checking only before deployment is not enough
The balance can fall while a job is running, and Hostinger says it does not send low-balance notifications. A job that looked affordable at launch can therefore reach a zero balance without an email or dashboard warning. For long work, record the starting balance, the displayed hourly rate, and the time you expect to check again. A human-set reminder or your own monitoring script cannot prevent every interruption, but it is safer than assuming Hostinger will alert you.
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How to top up Hostinger GPU credits
GPU funding is a manual dashboard action. Hostinger says GPU auto-top-up is unavailable, so add credits before the account reaches the point where the instance can be destroyed.
- Sign in to Hostinger and open Dev tools.
- Select GPU, then open Manage for the instance.
- Locate Current credits in the overview.
- Select Top up beside the balance.
- Choose the amount you want to add and select an available payment method.
- Complete the payment flow.
- Return to the GPU overview and confirm that the balance has increased before starting or extending a long job.
Top up based on the actual burn rate shown for your instance, not on a generic “GPU per hour” figure found elsewhere. Include enough headroom for the entire planned run and for time spent downloading data, installing dependencies, exporting results, or copying files out. Those activities still occur while the GPU resource is allocated.
What to do if the balance does not change
Do not launch another workload until the new balance is visible in the GPU overview. Reopen the instance’s Manage page and verify that you are looking at the same account and instance for which the payment was made. If the payment flow did not complete, follow the status shown by Hostinger’s billing interface rather than assuming that a failed or pending transaction supplied usable credits. The important operational test is the updated Current credits value.
Plan a job’s credit runway
A simple planning worksheet helps prevent an accidental shutdown:
- Starting balance: note the current credits immediately before deployment or before beginning the expensive phase of a job.
- Hourly burn: copy the credits-per-hour number displayed for that instance.
- Estimated runtime: divide starting credits by hourly burn to obtain a theoretical maximum.
- Safety margin: reserve credits for setup, checkpoints, validation, result export, and backup transfer.
- Recheck time: schedule a manual balance check well before the theoretical maximum is reached.
This calculation is intentionally conservative. It does not assume that Hostinger will pause billing while the GPU is underused, and it does not account for other products drawing from the same AI-credit balance. If a training job can run for many hours, split it into checkpoints so that a terminated instance does not erase all progress.
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Estimate not only how long the GPU computation will run, but also how long it will take to move the inputs, checkpoints, models, and outputs to storage you control. Hostinger’s GPU offering does not include persistent storage mechanisms or automated backups. A job that finishes successfully can still leave you with no recoverable result if the files remain only on the instance when credits expire or the resource is destroyed.
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What happens when Hostinger GPU credits reach zero
Hostinger’s stated behavior is immediate destruction. “The system destroys a Hostinger GPU instance immediately if your account credit balance reaches zero while the instance is running.” The documentation does not describe a grace period, temporary negative balance, or buffer that lets the workload finish.
Destruction means you should treat the instance as disposable once its balance is nearly exhausted. Do not wait for a final checkpoint, an interactive confirmation, or a warning message. Hostinger also says that it does not send low-balance notifications, so the customer must monitor the balance and fund the account manually.
Why an automatic top-up cannot save the instance
Hostinger documents that GPU auto-top-up is unavailable. A recurring funding rule therefore cannot be relied on to replenish the account at the exact moment a running GPU needs more credits. The safe sequence is to top up in advance, verify the new balance, and then continue the workload.
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Protect files before credits run out
Hostinger states that GPU instances do not include automated backups or persistent storage mechanisms. The legal agreement places responsibility for independent backups on the customer. In practical terms, anything that exists only on the GPU instance is at risk when the resource is destroyed, whether destruction follows a zero balance or your own cleanup action.
Before a long run, decide where each class of data will live:
- Source code and configuration: keep a copy in a version-control repository or on another machine.
- Datasets: retain the original in external cloud storage, a Hostinger VPS, or a local system.
- Model checkpoints: export checkpoints periodically rather than waiting for the final epoch.
- Generated results: copy completed artifacts and logs off the GPU before destroying it.
- Environment details: record package versions, startup commands, environment variables, and any custom system configuration needed to reproduce the job.
Hostinger specifically identifies a Hostinger VPS, cloud storage, or a local machine as possible destinations for copies. Test that a copied checkpoint or output can actually be opened from the destination. A transfer that was started but not verified is not a reliable backup.
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Understand the shared AI-credit balance
Hostinger documents one AI-credit balance shared by AI Builder, Agent, Reach, and GPU instances. A purchase made for one of these products can therefore change the funds available to another. Include every active AI service when you calculate how long a GPU balance will last.
Free-trial credits are spent first. Paid top-ups then enter the same shared balance. This does not change the GPU workflow: GPU funding still has to be initiated manually from the GPU page because GPU usage does not support auto-top-up.
Examples of shared-balance surprises
- A GPU calculation based on the visible balance may overstate the runway if another AI product is consuming credits at the same time.
- A trial balance may disappear before paid credits, because Hostinger applies free-trial credits first.
- Adding funds for an AI Builder project does not create a separate GPU wallet; the accounts draw from the shared pool.
For predictable GPU work, pause or account for other AI services, then recheck Current credits before deployment.
Stop Hostinger GPU billing safely
When the workload is finished, stop the hourly charge by destroying or terminating the GPU instance. Rebooting is not a billing control, and leaving the instance powered on for later convenience continues to consume credits.
- Save code, checkpoints, datasets, logs, and outputs to a VPS, cloud storage, or local machine.
- Verify that the copied files open correctly and that you have the configuration needed to resume elsewhere.
- Stop active jobs cleanly so they can finish writing checkpoints and logs.
- In Dev tools → GPU, open Manage for the instance.
- Use the dashboard’s destroy or terminate action and confirm the operation.
- Refresh the GPU page and verify that the instance is no longer allocated.
Because the instance is disposable and there is no documented pause mode that preserves its configuration without billing, record your setup before termination. If you need the same environment later, save an image, script, dependency list, or other reproducible configuration in storage outside the GPU resource.
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| Situation | Billing or credit effect | Required action |
|---|---|---|
| Instance deployed | Billing starts immediately. | Confirm the displayed GPU, size, region, and hourly credit rate before deployment. |
| Workload idle but instance allocated | Hourly charges continue. | Destroy the instance if you no longer need the resource. |
| Instance rebooted | Allocation remains; rebooting does not stop billing. | Use destroy or terminate to release the resource. |
| Balance topped up | Credits enter the shared AI-credit balance. | Return to the GPU overview and verify Current credits. |
| Free-trial credits available | Hostinger spends free-trial credits first. | Include all AI products when estimating the remaining balance. |
| Balance reaches zero while running | Hostinger says the system destroys the instance immediately, with no stated grace period. | Back up before the balance is exhausted and fund the account in advance. |
| Instance destroyed after completion | Further hourly GPU charges stop because the resource is released. | Confirm the instance no longer appears as allocated. |
Common billing mistakes and fixes
“I stopped the process, so why are credits still falling?”
Stopping a training or inference process does not release the allocated GPU. Check whether the instance still exists under Dev tools → GPU. If it is still allocated, destroy it after copying the files you need.
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“The machine is idle overnight.”
Idle time is billable. If no job needs the GPU, export your work and terminate the instance before leaving it unattended. Deploy a new instance when you are ready to resume, using your saved configuration.
“I expected a warning before shutdown.”
Hostinger says it does not send low-balance notifications. Set your own balance checks and top up before the estimated runway ends.
“The hourly price I found online does not match my dashboard.”
The rate varies by GPU, size, and region, and Hostinger has not provided a complete stable hourly table in the billing article. Use the deployment and instance screens for the selected configuration rather than a third-party figure.
“My results disappeared after the instance was removed.”
GPU instances have no automated backups or persistent storage mechanisms. Copy files externally during the run and verify those copies before termination or credit exhaustion.
A practical operating checklist
Before deployment
- Choose the GPU, size, and region, then note the credits-per-hour rate shown by Hostinger.
- Check Current credits and account for AI Builder, Agent, Reach, and other GPU usage sharing the balance.
- Confirm where datasets, checkpoints, logs, and final outputs will be stored outside the instance.
- Estimate runtime and reserve credits for setup, export, and backup transfers.
During the job
- Monitor the balance from Dev tools → GPU → Manage.
- Save checkpoints and copy important artifacts externally at intervals appropriate to the job.
- Top up manually before the planned runway is exhausted; do not wait for an automatic warning or auto-top-up.
After the job
- Stop processes cleanly and verify that outputs and configuration are copied elsewhere.
- Destroy the instance rather than rebooting or leaving it idle.
- Refresh the dashboard to confirm that the GPU resource has been released.
The key decision
Hostinger GPU is easiest to manage when you treat credits as a countdown attached to an allocated resource. The dashboard supplies the live balance and burn rate; the deployment screen supplies the configuration-specific price. Your responsibilities are to fund the shared balance manually, watch it because Hostinger does not provide low-credit alerts, export data because the instance is not backed up automatically, and release the GPU as soon as the work is complete.
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