The Render Network has introduced a new proposal, RNP-021, aimed at expanding its capabilities to support enterprise-grade GPUs for artificial intelligence (AI) and general compute use cases. This proposal builds on the earlier RNP-019, which integrated consumer-grade GPUs like the RTX 4090 and 5090 for similar purposes.

Submitted as a draft community proposal on October 17, 2025, RNP-021 seeks to incorporate high-performance GPUs such as the NVIDIA H100, H200, A100, and AMD MI300 series. The inclusion of these enterprise-grade GPUs is designed to enable the network to handle more demanding workloads, including large-scale AI model training and advanced video and image generation. This move aligns with the growing demand for scalable and cost-efficient computing solutions, as the global market for data-center GPUs is projected to reach $228 billion by 2030.

Enhancing Decentralized Compute Infrastructure

RNP-021 aims to transform the Render Network into a viable solution for enterprise-scale computing tasks. The proposal suggests onboarding enterprise-grade GPUs equivalent to up to 1,200 NVIDIA H200s, potentially delivering over 2.4 million TFLOPS of compute power. This expansion is expected to unlock new possibilities for creators, developers, and enterprises, offering an alternative to traditional cloud providers like AWS or CoreWeave.

Both consumer and enterprise nodes would share a single compute emissions pool, ensuring fair rewards across different hardware classes. The proposal also includes an increased reward baseline, from 10 RENDER to 25 RENDER per epoch for RTX 4090s, with multipliers for higher-end GPUs like the H200. This structure is designed to maintain consistent incentives while reflecting each GPU’s performance and market value.

Future-Proofing and Community Engagement

To future-proof the network, RNP-021 introduces a process for integrating 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 added to the network. Enterprise nodes would join a dedicated cohort, requiring verified hardware, reliable uptime, and clustering support for distributed tasks like video-model training.

Addressing potential GPU shortages and long lead times, the proposal grants 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 aims to keep the network competitive with centralized providers while ensuring reliable access for users and creators.

RNP-021 is currently open for community feedback and discussion. Interested parties can learn more or share their thoughts on the proposal here.

Why This Matters: Impact, Industry Trends & Expert Insights

The Render Network’s proposal RNP-021 aims to integrate enterprise-grade GPUs to enhance its capabilities for AI and compute workloads, potentially transforming its infrastructure to support more demanding tasks.

Recent industry reports indicate that the demand for AI and machine learning is driving the need for high-throughput, low-latency GPU deployments. This aligns with Render Network’s initiative to incorporate enterprise-grade GPUs to meet growing computational demands.

Recent industry research suggests that the integration of enterprise-grade GPUs in crypto networks is transforming them into scalable, high-performance infrastructures. This supports Render Network’s strategy to offer competitive alternatives to traditional cloud providers by leveraging advanced GPU technology.

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