Independent product intelligence · Worldwide · 2026-05-01 → 2026-07-31
Petals enables users to run large language models like Llama 3.1 and Mixtral collaboratively, distributing the load across a network of consumer-grade GPUs.
Traffic & engagement
Search demand
AI referral visibility
Product profile
Traffic makes more sense when you can connect it to the actual product promise.
“Petals”
Petals enables users to run large language models like Llama 3.1 and Mixtral collaboratively, distributing the load across a network of consumer-grade GPUs.
4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.
Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.
Canonical website: https://petals.dev
Observed across 1 discovery source.
Research questions
Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.
Petals offers a collaborative, distributed system for running LLMs, allowing users to load part of a model and join a network serving the rest. It provides an API-like interface with the full flexibility of PyTorch and 🤗 Transformers, and supports running on consumer-grade GPUs or Google Colab.
Within its category of Developer & AI Platform, Petals has a domain authority of 20, which is slightly below the median domain authority of 22 for the 2,619 products in that category.
Petals enables users to run large language models like Llama 3.1 and Mixtral collaboratively, distributing the load across a network of consumer-grade GPUs. This approach allows individuals to access and fine-tune powerful LLMs without needing massive compute resources.
Petals is used to generate text with models like Llama 3.1 (up to 405B), Mixtral (8x22B), and BLOOM (176B), and to fine-tune them for specific tasks. It is suitable for building chatbots and interactive applications, as it provides enough inference speed (e.g., up to 6 tokens/sec for Llama 2 70B) for such use cases.
Petals is designed for developers and users who want to run or fine-tune large language models without relying on expensive, centralized APIs or hardware. It offers the flexibility of PyTorch and 🤗 Transformers for anyone who needs custom model paths or access to hidden states.
Petals is a platform that enables collaborative, distributed running and fine-tuning of large language models, categorized as a Developer & AI Platform.
Behind the lock
Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured