FAQ

An On-Demand instance is a non-interruptible virtual machine that you can deploy and terminate at any time, paying only for the compute time you use.

A Spot instance is a cost-effective virtual machine that uses unused cloud capacity. It offers discounts of up to 90% compared to On-Demand instances, but it can be interrupted if the capacity is needed by other users. Spot instances are ideal for workloads that are flexible and can tolerate interruptions, such as batch jobs, data analysis, or fault-tolerant applications.

Each Pod has an hourly cost depending on the provider and GPU type. Your Prime Intellect credits are deducted every minute while the Pod is active. If your credits run out, your Pods will be automatically deleted. We highly recommend setting up our auto-top-up feature in your billing settings to ensure balances are automatically topped up as needed.

Secure Cloud providers are established data centers offering higher reliability and dedicated resources. Community Cloud providers (e.g., Akash, Tensordock) can be more cost-effective but may be less reliable and have less predictable uptime. Community Cloud instances may sometimes be reclaimed or have intermittent issues.

We are constantly adding new providers! You can find the current and upcoming list of providers here.

Instances typically launch within a few minutes, but the exact time may vary depending on the provider. More detailed information on spin-up time is shown on your instance card.

We don’t provide formal SLAs at this time, as the underlying infrastructure relies on various providers. If you experience repeated downtime or unreliable performance, contact support. We’ll work with the provider to resolve the issue or offer refunds/credits when disruptions stem from provider-side instability. For more reliability, choose Secure Cloud providers or verify uptime and past performance before deploying long-term workloads.

You can pause and resume instances on supported providers (currently Runpod and Tensordock), allowing you to save state and continue later at a lower cost than keeping the instance running. When resuming, note that GPU resources may not be immediately available, leading to wait times. Look for the “Pause” button on the instance details page. ⚠️ Important: If you terminate (rather than pause) your instance, you will lose all data.

For paused instances only, data can be persisted in a special directory that is shown in your instance details in the dashboard. For example, Runpod stores persistent data in the /workspace directory. Note that this only works when pausing an instance - if you terminate the instance, all data will be lost. Always back up critical data to external storage (e.g., S3) before terminating or pausing.

No, once an instance is terminated, all data stored on it is permanently deleted and cannot be recovered.

While most providers let you configure storage during instance creation, very large volumes may not always be honored. If your requested storage isn’t fully available or doesn’t match what’s provisioned, contact support. We’ll verify the provider’s limitations and may offer guidance or alternative providers that can meet larger volume requirements.

Yes. Many providers allow you to configure CPU, RAM, and storage during instance creation. However, some have limits. Hover over the pricing or configuration fields on the instance creation page to see what’s available. We’re also adding filters to search by CPU, RAM, and storage soon.

First, ensure you have the correct SSH key from your instance’s “SSH Connection” button and set permissions on your local machine correctly with chmod 400 private_key.pem. For Jupyter notebooks, simply click the provided link on your instance page to access the notebook interface directly in your browser. If you still face issues, contact support with error details.

You can click the Port Information button on your instance to see which ports are open:

Yes. Certain providers (e.g., Latitude, Cudo, Scaleway, Hyperstack, Oblivus, Massedcompute, Datacrunch) already have open ports. We’re also adding the ability to specify custom port mappings. Check provider details or the FAQ to see if port configuration is supported. If not, you may need to wait for the upcoming port-exposure feature rollout.

Yes, you can deploy custom Docker images through our templates feature. When creating an instance, select “Custom Template” and specify your Docker image. You can also save and reuse your custom environments as templates for future deployments. Check our documentation for detailed instructions on using custom images and managing templates.

Some providers support docker-in-docker configurations and system-level services, while others do not. Check the provider’s documentation or contact support if you encounter issues. We’re working on better clarifications and tutorials to help you understand what’s supported in your chosen environment.

If your instance fails due to provider issues (such as failing to start, crashing early, or being impossible to terminate from your dashboard), contact support with the instance details. We typically provide refunds or credits when the issue stems from our system or provider instability. Please contact us in the support chat by typing REFUND as your first word, then describe your issue in detail and include screenshots.

When you sign up or top up credits, look for the promo code input field. If you’ve already signed up, the promo code field is typically found in the billing/top-up section. If you have trouble finding it, contact support and we’ll manually credit your account.

We’ve introduced a “Teams” feature where you can invite multiple users and set a dedicated billing email. Create a team from your dashboard’s team settings, add members, and specify the billing email (e.g., billing@company.com) so that all invoices are sent there. This helps consolidate usage and manage costs for multiple users under one account.

Currently, most billing occurs in USD and via standard payment methods. If you need invoicing in other currencies or want to explore alternative digital payment options, please contact support. We’re actively considering these features and may arrange manual invoicing or special payment methods in the future.

If your instance fails to launch or remains “pending” for an extended period, first try terminating it and creating a new one. If the problem persists, contact support with the instance details. In cases where the issue is on the provider’s side, we can often provide refunds or credits.

Our Multi-Node clusters are GPU instances in our cloud featuring NVIDIA H100 SXM5 GPUs with 80GB memory each, available in configurations of up to 256 GPUs per cluster. These instances are deployed on our Secure Cloud infrastructure with the following specifications:

Premium Configuration:

• 3.2Tbps INFINIBAND connectivity
• 104 CPU cores per node
• 16TB storage per node
• ~$52.80/hr

Value Configuration:

• 100Gbps ETHERNET connectivity
• 104 CPU cores per node
• 12TB storage per node
• ~$40.80/hr (CHEAPEST CLUSTER option)

All clusters are hosted in United States data centers with an estimated spin-up time of ~30 minutes. Those instances can spin up on-demand. For further custom cluster options use the new “Custom GPU Quote” feature.

You can follow our step-by-step guide on how to deploy and use a multi-node cluster for your use case here.

Yes, you can reserve larger instance clusters for longer durations to ensure availability and reduce costs. Use the “Custom GPU Quote” feature in your dashboard to request a quote for long-term reservations. You can also reach out to contact@primeintellect.ai for additional information.

We are actively expanding our network of GPU providers, including both individual compute providers and larger cloud platforms. For more information, please contact us at contact@primeintellect.ai.