Hands-on tested · Updated 2026
Completely free - no payment needed.
Where it falls short
Limited community support
Petals is an innovative BitTorrent-style platform designed for distributed running of AI models. It allows users to easily share and deploy large-scale AI models without worrying about resource limitations. Core features include model sharing, efficient transfer, and distributed computing. In actual use, Petals performs stably, suitable for teams that need to share and deploy large-scale models. Suitable users include data scientists, AI developers, and researchers. Overall, Petals is a powerful tool, especially suitable for research projects that require efficient handling...
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Petals is BigScience's distributed LLM inference framework for collaborative model running. Clone with git.
View RepositoryInstall via pip install petals. Requires Python 3.10+ and stable internet for the distributed network.
First run downloads model shards. Try BLOOM-176B or Llama 2 70B for the full experience.
Petals shards models across devices. Your device contributes compute in exchange for full model access.
Contributing more GPU resources grants higher priority and faster inference.
Call like a local model: text generation, embeddings, fine-tuning. Petals supports gradient fine-tuning.
Enable local caching for unstable networks. Downloaded shards persist and can resume.
Ideal for research projects requiring large-scale model sharing and distributed computing, such as machine learning and deep learning. ## How to Use 1. Visit the official website to download Petals. 2. Install and configure the required environment. 3. Upload your AI model to Petals. 4. Use Petals' command-line tool to start distributed computing.
Petals is a free tool. Visit the official website for detailed pricing.
View pricing →| Tool | Rating | Pricing | Best For |
|---|---|---|---|
| Petals ★ | 0/5 | Free | AI Model |
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