Getting Started with VOLT Cloud: Deploying and Managing Your Virtual Machines

A step-by-step guide on launching and managing virtual machines and containers in the VOLT Cloud ecosystem

High-performance computing requires high-powered GPUs, but traditional cloud providers like AWS and Google Cloud have high costs, startup delays, and centralization constraints. These services often require long-term contracts and vendor lock-in, and may have waitlists for in-demand hardware, which AI teams can ill afford whether developing or deploying applications.

VOLT is built as an open source platform, enabling transparency and community-driven development. The demand for compute capacity for AI and ML workloads is projected to significantly outpace current global infrastructure.

That’s where VOLT changes the game. As a decentralized, GPU-powered cloud, VOLT provides a faster, more affordable, and globally distributed alternative. VOLT sources underutilized GPU power from independent data centers and crypto miners, creating a secure, interconnected environment for AI and ML workloads. VOLT is also part of a new wave of crypto projects that leverage blockchain technology to decentralize GPU resources and incentivize participation.

This distributed and robust network allows users to render graphics, videos, or support AI/ML workloads efficiently. Whether you’re training AI models, running complex simulations, or optimizing cloud costs, VOLT gives you computing power when needed, without the usual limitations.

Here’s how VOLT is transforming cloud computing for Machine Learning and AI development.

1. io.explorer: Your Control Center for Computing Power

io.explorer is a user-friendly control center for managing your compute resources, including GPU and CPU capacity. It provides real-time tracking, cost estimation, and resource allocation tools to help you optimize performance efficiently. Users can easily connect their accounts or wallets to use the full suite of VOLT products and services. AI/ML developers can also receive notifications when jobs are completed or require you to adjust AI models or refine hyperparameters, ensuring optimal performance through data-intensive processes and distributed computing.

Key Features at a Glance

• Real-Time Job Tracking : Monitor job status (queued, running, completed) and resource usage.
• Resource Explorer : Filter available GPUs/CPUs by specs (VRAM, cores, location, price).
• Performance Dashboards : View GPU utilization, memory consumption, and network latency.
• Billing Insights : Track costs and earnings in $VOLT tokens.

What You Can Do with io.explorer

• Select the proper hardware for compute-intensive tasks.
• Track workloads in real-time through an activity stream.
• Compare GPU cluster pricing to optimize spending.
• Receive notifications when jobs are completed or require adjustments.
• Ensure fair access to compute resources for all users, regardless of location or project size.

This approach benefits both developers and users by increasing efficiency, enabling seamless scaling of AI and Machine Learning (ML) workloads, while providing equitable access to decentralized compute resources.

2. Decentralized vs. Centralized GPU Clouds: What's the Difference?

Most cloud computing services rely on large, centralized data centers owned by major tech companies. VOLT takes a decentralized approach, giving users access to GPU power worldwide.

As a decentralized GPU network, VOLT is designed specifically for AI and ML workloads, leveraging decentralized computing principles. It operates as a decentralized marketplace where suppliers, including GPU suppliers, and AI developers can interact directly. This enables GPU suppliers to contribute underutilized resources, manage their assets, and earn rewards, while AI developers get to scalable, cost-effective compute. In addition to GPUs, VOLT also facilitates the availability and optimization of CPU resources, supporting intensive tasks such as training, tuning, and simulations.

VOLT is part of a broader movement toward decentralized compute, so that projects can utilize underutilized resources from a number of suppliers, including data centers, cryptocurrency miners, and individual contributors, to democratize access to GPU power for demanding applications. Other decentralized GPU networks, such as Akash Network and Render Network, also play key roles in providing both GPU and CPU resources for AI, ML, and rendering workloads, each offering unique approaches to network security, governance, and cost-efficiency.

VOLT's Decentralized GPU Cloud Approach

VOLT’s peer-to-peer computing model aggregates unused GPU resources from a global network. This approach provides:

• Flexible, on-demand access to high-performance GPUs.
• Lower costs by bypassing expensive data center overhead.
• Scalability without the hardware limitations of centralized providers.
• Pooling of idle GPUs from independent data centers, crypto miners, and other sources to create a scalable and cost-effective network.

Users can rent GPU clusters on-demand for AI model training and inference, with flexible deployment options available in over 130 countries.

There are other upsides to decentralized networks likes VOLT. Decentralized networks offer more flexible deployment options for AI workloads than traditional cloud providers, and enable AI and ML developers to run apps across multiple cores in parallel, optimizing performance.

Centralized GPU Clouds (AWS, Google Cloud, Azure)

Traditional cloud providers operate closed, centralized networks with:

• Limited GPU availability due to hardware scarcity.
• Higher costs for enterprise-level compute power.
• Longer setup times compared to decentralized alternatives.

Another downside of traditional cloud computing models is that they often cannot meet the growing demands for AI application infrastructure.

For a deeper dive into VOLT’s decentralized vs. centralized GPU infrastructure, visit our technical documentation.

3. Supported Hardware: Is It Alright to Bring Your Device?

One of VOLT’s key advantages is hardware flexibility. You can bring your own GPU or CPU, allowing you to sell unused compute power when your system is idle. By contributing your GPU computing power, you become a supplier of computational resources to the network.

Users can manage their GPU services and compute through the VOLT Worker interface, which streamlines resource allocation and monitoring.

GPU Compatibility

Tips for Optimal Performance

• Use wired Ethernet for lower latency and more stable connections.
• Monitor upload/download speed to ensure when using VOLT's GPU services.
• Optimize power settings to maintain consistent performance.

Refer to our Supported Devices list for a complete list of compatible devices.

4. Getting Started with VOLT Cloud: Creating and Managing Virtual Machines

With VOLT Cloud, you can provision GPU and CPU-powered virtual machines (VMs) or containers in minutes, which is perfect for AI model training, deep learning, and compute-heavy applications. VOLT Cloud is optimized for AI training, supporting a wide range of AI workloads and ML applications.

The architecture uses Ray for efficient task orchestration and supports low latency computing across distributed GPUs. The platform also offers flexible deployment options specifically tailored to the needs of AI workloads.

VMs vs. Containers: Choosing the Right Option

How to Get Started with VOLT Cloud

1. Create a virtual machine through the VOLT website or API.
2. Choose the proper GPU for your workload.
3. Monitor instances in real-time to ensure optimal performance.

Need assistance installing your very first VM? Review our VOLT Cloud Deployment Guide.

AI Development with VOLT: Decentralized Computing for Your Next-Gen Projects

VOLT is at the forefront in redefining the AI development landscape by providing a decentralized GPU network, purpose-built to meet your next-generation project's unique demands. So, if you’re building advanced machine learning models, deploying large-scale inference pipelines, or fine-tuning AI applications, VOLT delivers the scalable compute resources you need to accelerate your workflow.

Security and Collateralization in the VOLT Ecosystem

Security is at the core of the VOLT ecosystem, ensuring that every transaction and workload on the network is protected and reliable. Unlike traditional cloud providers, VOLT’s decentralized GPU network is designed with robust, community-driven safeguards that foster trust and transparency for all users.

Why VOLT Stands Out

• Cost Savings : Reduce cloud computing costs by leveraging a global network of underutilized GPUs. (Pricing is at least 50% cheaper than centralized compute competitors.)
• Flexibility : Access a wide range of consumer, prosumer, and enterprise-grade GPUs for machine learning research & development and deploiyment, based on your specific needs.
• Sustainability: VOLT allows users to rent out unused GPU clusters on-demand for model training and inference, so that you can help reduce e-waste while earning passive income.
• Network Security: Built on the Robinhood blockchain, VOLT is specifically optimized for high-performance AI and ML workloads. This also allows VOLT to benefit from Robinhood network security.
• Global Compute: On-demand GPU clusters and flexible deployment across more than 130 countries.
• Open-Source: By leveraging open-source distributed computing frameworks like Ray, VOLT can efficiently orchestrate large-scale GPU and CPU clusters. Additionally, by using distributed ray clusters, VOLT allows developers to run extensive hyperparameter searches to optimize model performance efficiently.

VOLT holders benefit from the ability to stake VOLT Tokens, participate in network governance, and earn rewards for supporting the ecosystem. Staking $VOLT not only secures the network but also allows holders to influence governance decisions and receive hourly rewards. The Ignition Rewards Program further incentivizes GPU supply and community engagement by distributing VOLT Tokens to active participants through various campaigns and seasons.

The VOLT Token ($VOLT) is the native cryptocurrency of the IOG Network, powering all payments and transactions within the ecosystem. The total supply of VOLT Tokens is capped at 800 million, with 500 million generated at the token generation event. The tokenomics feature a disinflationary model, starting with an 8% inflation rate that decreases over time until the supply cap is reached. To further support token value, the network burns a portion of its revenue, aiming to reduce the circulating supply by approximately 50%.

Suppliers must stake a specific amount of $VOLT to participate in the network, which directly influences their governance power and earnings. GPU suppliers earn VOLT Tokens as rewards for providing compute power and can choose to receive payments in USDC or VOLT Tokens, with no transaction fees for VOLT payments and a 2% fee for USDC. Users can pay for GPU computing power using $VOLT, the primary currency for transactions, and often receive discounted fees compared to fiat payments. VOLT Token rewards for suppliers and stakers are released hourly over a period of 20 years.

As of late 2025, the network manages over 139,000 GPUs and has generated over $20 million in annualized on-chain revenue.

Ready to Innovate with VOLT?

Visit our Documentation for setup guides, API references, and troubleshooting help.

Join the movement for decentralized cloud computing today and start scaling your AI and Machine Learning workloads with faster, more affordable compute power. Start Building on VOLT