Expanding the Render Compute Initiative: RNP-021 Proposes Support for Enterprise-Grade GPUs

RNP-021 expands RNP-019 to support enterprise-grade GPUs for AI and general compute use cases.

Following community proposal RNP-019, which introduced consumer-grade GPUs (like the RTX 4090 and 5090) to power AI and general compute workloads, a new proposal, RNP-021, takes the next step toward scaling the Render Network for higher performance computing.

This new proposal, submitted as a draft community proposal on October 17, 2025, expands the framework of RNP-019 to include enterprise-grade GPUs such as the NVIDIA H100, H200, A100, AMD MI300 series, and others. By doing so, the network could serve more demanding workloads, such as large-scale AI model training or advanced video and image generation, via a decentralized compute infrastructure model.

Serving The Needs of a Growing Category

The global market for data-center GPUs is projected to reach $228 billion by 2030, driven by rapid growth in AI, machine learning, and high-performance computing (HPC). As more organizations look for scalable, cost-efficient compute, the Render Network’s decentralized model offers an alternative to traditional cloud providers like AWS or CoreWeave.

While RNP-019 laid the foundation by enabling consumer-grade GPU operators to lend their spare capacity to the network for compute, RNP-021 responds to enterprise demand, where workloads can require 10 to 100 times more compute power than standard AI inference tasks.

The proposal aims to give the Render Network the ability to handle these enterprise-scale jobs, such as:

• Training large foundation models (LLMs, image, or “world” models)
• Real-time AI inference for chatbots, image generation, or video synthesis
• Video and image generation models like Seedream or Flux, which require high memory and parallel compute

In particular, given the long history, expertise, and reputation of the Render Network in enabling content creators and artists, this proposal represents a step that could transform decentralized compute into a viable, scalable solution for the next generation of AI, video, and image innovation.

How RNP-021 Expands on RNP-019

RNP-021 builds directly on the technical and reward frameworks of RNP-019, introducing several key updates:

1. Enterprise Hardware Support

The network would onboard enterprise-grade GPUs equivalent to up to 1,200 NVIDIA H200s, with flexible combinations of approved hardware (H100s, A100s, MI300Xs, etc.). This expansion could deliver more than 2.4 million TFLOPS of compute power for AI workloads, unlocking new possibilities for creators, developers, and enterprises.

2. Unified Compute Rewards Pool

Both consumer and enterprise nodes would share a single compute emissions pool, ensuring fair rewards across hardware classes. RNP-021 proposes an increased reward baseline, from 10 RENDER to 25 RENDER per epoch for RTX 4090s, with multipliers for higher-end GPUs like the H200 (×5).

This structure keeps incentives consistent while reflecting each GPU’s performance and market value.

3. Dynamic Hardware Inclusion

To future-proof the network, RNP-021 introduces a process for adding new chips and architectures over time. Through standardized benchmarking and community review, emerging models, such as Groq LPUs or future AMD and Intel accelerators, could be integrated into the network.

4. Enterprise Cohort and Node Requirements

Enterprise nodes would join a dedicated enterprise cohort, requiring verified hardware, reliable uptime, and clustering support for distributed tasks like video-model training.

5. Optional GPU Procurement by the Foundation

To address GPU shortages and long lead times, RNP-021 gives the Render Network Foundation limited authority to procure enterprise-grade GPUs in bulk. These nodes would operate under a cost-based, utilization-only model, ensuring capacity for large jobs without increasing idle-time emissions.

This approach helps the network stay competitive with centralized providers while ensuring reliable access for users and creators.

The Bigger Picture

RNP-021 represents the next stage of evolution for the Render Network AI and general compute initiative. If approved, this proposal would:

• Expand total available compute by up to 1,200 H200-equivalent GPUs
• Create new earning opportunities for node operators running high-end hardware
• Support advanced workloads like video model training, scientific simulations, and image generation
• Strengthen the Render Network’s position as a decentralized alternative to cloud hyperscalers to support general use cases, including next-level AI image and video generation

Share your Feedback

RNP-021 is currently open for community feedback and discussion.

To learn more or share your thoughts, visit the #rnp-021 channel on Discord and provide feedback on the RNP-021 proposal.