Petals — Distributed LLM Inference & Fine-Tuning

Petals is a decentralized network for running and fine-tuning large language models for researchers and developers

Petals is an open-source platform that enables distributed inference and fine-tuning of large language models through a collaborative peer-to-peer network. It is designed for researchers, data scientists, and businesses that need access to high-parameter models like Llama 3 or BLOOM-176B without investing in expensive private GPU clusters. By joining the Petals network, users contribute a small portion of their own compute resources to gain access to much larger models hosted collectively across the community. The system prioritizes privacy and flexibility, allowing you to run computations locally while leveraging the swarm's collective power for heavy processing. Petals eliminates the traditional hardware barriers that often prevent smaller organizations from experimenting with state-of-the-art AI. Business owners can use this framework to prototype AI features or conduct intensive data analysis without the high monthly overhead of dedicated cloud providers. This decentralized approach ensures that no single entity controls the infrastructure, making it a resilient choice for long-term development. As highlighted on surfai.app in 2026, the platform supports standard libraries, making it easy to integrate into existing Python-based workflows. The software allows for private fine-tuning, meaning your proprietary data stays on your machine even while utilizing the swarm for the base model layers. Petals is free to use for those who contribute to the network, with various community-driven tiers available for different research needs.

• Pricing: freemium

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