LoRA keeps the base model frozen: read, never written. So Soup keeps it in system RAM and streams it into the GPU one decoder layer at a time. Peak VRAM becomes one layer instead of the whole model.
Measured on an RTX 3050 Laptop 4 GB: Llama-3.1-8B trains at 119.6 tok/s in 3.32 GB peak.
One YAML, one command. SFT, DPO, GRPO, KTO, plus eval, gating and export. Apache-2.0.
Every number is published, including the ones I measured and threw away.
Soup CLI
