How does the Render Network plan to scale its infrastructure?
From the outset the Render Network has made it a priority to protect artists’ valuable IP and creations while upholding performance and security. We have a waitlist of keen community participants willing to offer GPU power.
The Render Network Foundation was established in 2023 to manage governance of the Render Network and promote usage. In 2024 and 2025, the foundation invested in hiring key roles to build initiatives that would increase awareness and usage of the protocol including investing in brand awareness efforts, community management and communication processes, partnerships that promote usage, and operational workstreams to support all these initiatives.
Is the Render Network suitable for workloads outside of traditional 3D rendering jobs, such as AI inference and training?
As AI-related workloads, including inference, edge and offline machine learning, and other tasks become more feasible on distributed consumer-grade GPUs, we expect to see customers take advantage of our protocol’s scale and competitive pricing. We are already seeing demand emerge for running AI and general compute jobs on Render Network nodes. This was a key driver for the community’s approval of RNP19 in April 2025, which will establish a sub-network of dedicated compute nodes optimized for AI and general compute workloads.
What role do you envision Render Network playing in the upcoming wave of AI-native 3D content generation tools and will your infrastructure evolve to support real-time AI workflows?
In addition to building a dedicated compute sub-network, the Render Network will continue to service the needs of our community of motion graphics artists via its rendering network. As those needs evolve to include AI models and other forms of rendering we expect our network to continue to evolve to support these. Our largest partner, OTOY, has already signaled its intent to expand its integration of generative tools and neural rendering into Octane and into its new property OTOY.ai. OTOY has also signaled its intent to run as much of this as possible on the Render Network.
How does your decentralized approach mitigate risks like data privacy and model bias compared to centralized AI platforms?
Decentralization is well suited towards individual control of user data as users are better equipped to make decisions regarding how and how much of their data is accessed. Given the artist and creator community we serve, we are particularly invested in supporting copyright protection wherever possible. There’s a growing shift towards user-owned agents and AI tooling that allow users and creators to maintain a level of control over their data. The Render Network is well suited to provide a decentralized network of compute nodes to power these emerging platforms.
Which rendering engines are available on the Render Network?
The network currently supports Octane Render, Redshift and Blender Cycles. See this guide on getting started as an artist: https://know.rendernetwork.com/getting-started/how-to-get-started
How does the Render Network empower individual artists or small studios to compete and create high quality production level creations?
At its core, the network allows artists and creators to access hundreds of GPUs simultaneously to handle the compute necessary for 3D rendering. Running jobs locally might require purchasing comparable GPUs individually, a cost-prohibitive barrier for most artists who are not large studios. In addition, our simple usage pricing model means artists and creators don’t need to rent and manage costly, complex cloud infrastructure. Our platform provides a range of methods for submitting rendering jobs; solo developers can start directly uploading simple jobs at rendernetwork.com.
For larger end users we have a separate upload and download manager tool which can greatly help streamline the joint production process. They can integrate directly to our Render APIs allowing them to directly integrate within existing workflows.
How is pricing calculated in real time and can users estimate rendering costs before submitting a job?
OctaneBench is the benchmark used on the Render Network. Jobs are priced in a fixed Euro OctaneBench rate per tier depending on whether they need to prioritize speed or cost. Nodes are scored and are allocated jobs accordingly. https://know.rendernetwork.com/getting-started/how-to-get-started/estimate-job-costs-prior-to-rendering
How are node operators incentivized to contribute their hardware’s capacity to the network and maintain high-performance standards?
The Render Network was developed to increase access to rendering compute power for artists and creators without sacrificing speed, scale, or budgets. This is possible via a network of distributed node operators who provide idle compute power to the network via consumer-grade GPU hardware and are rewarded for it.
Rendering is currently the highest paying commercial GPU activity, exceeding the typical rewards generated from compute and mining activity. Our model targets the surplus of the millions of existing high-end consumer GPUs which are currently idle or underutilized. On average, nodes have historically generated rewards that exceed the costs of running the node, primarily the cost of electricity. Separate from the rendering network the Render Compute Network, a dedicated network for AI related workloads, availability rewards are geared to incentivize stronger processors and higher bandwidth.
How are node operators paid for their compute power?
There is an amount of emissions allocated per epoch set aside for rewarding node operators. Nodes are issued rewards on the basis of their availability throughout the epoch and their share of work completed. Availability rewards are distributed according to uptime per each active node connected to the network using a weighted points system—not just total computing power—with the aim to equitably distribute RENDER rewards. For more information on our Burn and Mint Model (BME): https://github.com/rendernetwork/RNPs/blob/main/RNP-001.md
More information about availability rewards: https://github.com/rendernetwork/RNPs/blob/main/RNP-015.md