6 papers
Arcee Trinity Large Technical Report
Varun Singh, Lucas Krauss, Sami Jaghouar +23
We present the technical report for Arcee Trinity Large, a sparse Mixture-of-Experts model with 400B total parameters and 13B activated per token. Additionally, we report on Trinit…
INTELLECT-3: Technical Report
Prime Intellect Team, Mika Senghaas, Fares Obeid +20
We present INTELLECT-3, a 106B-parameter Mixture-of-Experts model (12B active) trained with large-scale reinforcement learning on our end-to-end RL infrastructure stack. INTELLECT-…
TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference
Jack Min Ong, Matthew Di Ferrante, Aaron Pazdera +5
Large language models (LLMs) have proven to be very capable, but access to frontier models currently relies on inference providers. This introduces trust challenges: how can we be…
Prime Collective Communications Library -- Technical Report
Michael Keiblinger, Mario Sieg, Jack Min Ong +2
This report presents the Prime Collective Communications Library (PCCL), a novel fault-tolerant collective communication library designed for distributed ML workloads over the publ…
INTELLECT-2: A Reasoning Model Trained Through Globally Decentralized Reinforcement Learning
Prime Intellect Team, Sami Jaghouar, Justus Mattern +11
We introduce INTELLECT-2, the first globally distributed reinforcement learning (RL) training run of a 32 billion parameter language model. Unlike traditional centralized training…
INTELLECT-1 Technical Report
Sami Jaghouar, Jack Min Ong, Manveer Basra +9
In this report, we introduce INTELLECT-1, the first 10 billion parameter language model collaboratively trained across the globe, demonstrating that large-scale model training is n…