Unsloth Enables Local Training of Decision Models with Under 4GB VRAM

Unsloth announced that open-source LLMs like Qwen and Gemma can be fine-tuned into decision models locally using only 3-4GB VRAM, boosting Qwen3.5 0.8B's accuracy from 20.7% to 74.3% across three decision benchmarks.

2026-10-08 ~ 2026-10-08 · 2 related posts

• Unsloth fine-tunes Qwen3.5 0.8B on 4GB VRAM, lifting decision accuracy from 20.7% to 74.3% — kalyan_kpl · 2026-10-08
• Unsloth trains local decision models on 3GB VRAM, lifting accuracy from 30% to 78% — evilsocket · 2026-10-08