Prime Intellect
Prime Intellect provides the open stack for self-improving agents, enabling decentralized training and global collaboration in AI compute, code, and capital.
At a Glance
- AI Research Labs
- Startups
- Decentralized AI Community
- Enterprise AI Developers
AI Tools by Prime Intellect
(1)Verifiers
LLM RL Training Environment Library
Discussions
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Latest News
Prime Intellect releases INTELLECT-3: A 100B+ MoE trained with large-scale RL
INTELLECT-2 Release: The First 32B Parameter Model Trained via Decentralized Reinforcement
INTELLECT-1: The First 10B Parameter Language Model Collaboratively Trained Across the Globe
Prime Intellect raises $15M led by Founders Fund to build the open superintelligence stack
Products & Services
A decentralized GPU exchange and marketplace where users can rent and deploy GPU clusters (H100s, A100s, etc.) at competitive rates.
A 10-billion-parameter language model collaboratively trained across the globe using decentralized compute.
A 32-billion-parameter reasoning model trained via decentralized reinforcement learning.
A 100B+ Mixture-of-Experts language model trained with large-scale RL, available via Vercel AI Gateway.
Market Position
Prime Intellect positions itself as the decentralized alternative to centralized AI labs and cloud providers, focusing on transparency and global accessibility.
Leadership
Founders
Vincent Weisser
Co-founder & CEO. Previously a founder/executive in the Web3 and Decentralized Science (DeSci) space, including roles at Molecule and Bio-AI projects. Focused on the intersection of AI and global collaboration.
Johannes Hagemann
Co-founder & CTO. AI research background with a focus on machine learning and decentralized training frameworks.
Executive Team
Vincent Weisser
Co-founder & CEO
Background in Web3, DeSci, and Bio-AI. Former executive at Molecule.
Johannes Hagemann
Co-founder & CTO
AI researcher focused on decentralized infrastructure and model training.
Board of Directors
Founding Story
Prime Intellect was started with the belief that decentralizing AI development is crucial for driving innovation and preventing a centralized monopoly. The founders aimed to make frontier AI training accessible by leveraging globally distributed compute resources.
Business Model
Revenue Model
Decentralized compute marketplace commission (taking a spread on GPU rentals) and potentially usage-based API access for proprietary models.
Pricing Tiers
H100 GPUs typically fluctuate between $1.20 and $1.80 per hour.
Lower-cost compute for non-critical training workloads.
Target Markets
- AI Research Labs
- Startups
- Decentralized AI Community
- Enterprise AI Developers
- Decentralized AI model training
- Cost-effective GPU compute access
- Open-source AGI research
- Collaborative AI development
- Zapier
- Ramp