SILX AI — Open Foundation Models for Long-Context Intelligence
Novel architectures. Millions of tokens of context. Trained on decentralized compute. All open-weight.
What We Work On
Novel architectures and training methods that move the field forward.
Linear Attention
Standard transformers scale quadratically. Our Quasar architecture uses continuous-time attention that scales linearly — handling millions of tokens at a fraction of the compute.
Decentralized Pretraining
We train on Bittensor's distributed compute network. Miners compete to produce the best model checkpoints, making frontier-class training accessible without centralized GPU clusters.
Open Weights
Every model we release ships with full weights under Apache 2.0. No gated access, no waitlists. Download from Hugging Face and deploy on your own infrastructure.
Quasar
Our foundation model series for open, long-context intelligence.
Quasar-3B-A1B-Preview
LivePreview MoE foundation model for long-context understanding and reasoning.
Latest from Quasar
Partnership updates, research notes, and model progress from the SILX team.
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