RHEA: A 1B Event-Driven Architecture Trainable on Consumer Hardware
zemondza · reddit · 2026-08-24
An independent developer shares an experiment with a novel neural network architecture called RHEA.
Core Features:
- Event-Driven: Based on event-driven responses rather than a conventional Transformer stack.
- Non-Standard Structure: Does not rely on standard Attention/MLP blocks, experimenting with different internal processing methods.
- Consumer Hardware Friendly: Optimizations allow training a roughly 1B-parameter RHEA model on an RTX 5070 Laptop GPU (8GB VRAM).
Experimental Goals:
- Explore how far this architecture can be pushed without access to large GPU clusters.
- Investigate training behavior, efficiency, and scaling characteristics.
It is currently a research project focused on observing how the event-driven approach behaves as the model scales.
Related event: RHEA: Training 1B-Parameter Models on 8GB VRAM(2 posts)→
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