Frugal AI

Making the impossible possible under constrained supply. Frugal AI is about getting more from the accelerators you can actually get — through model compression onto more available instances, compute optimization, and smaller fine-tuned open-weight models that meet your quality bar at a fraction of the cost.

What this section will cover

• Model compression and quantization (FP8/FP4) to fit larger models on smaller or more available instances
• Compute and serving optimization for open-weight models
• Right-sizing accelerators to workload requirements
• Cost-per-value framing: moving beyond cost-per-token

Work in progress

We're building out this section with hands-on, field-validated guides. Contributions are welcome via GitHub.