Dev distills 157GB DeepSeek V4 Flash into 4B model in 26h on DGX Spark, 22ms per judgment
alexcovo_eth · x · 2026-09-20
Developer taroleo shared a full distillation run: using a DGX Spark for 26 hours, he distilled the 157GB DeepSeek V4 Flash into a 4B local model. At 1/20 the size, it beat the teacher's instant-response mode, with 22ms per judgment — all running locally.
Quoting this, studioyebisu argues there's a big business in selling custom-distilled, domain-specific local LLMs to enterprises: generic APIs have weak spots in response style and judgment accuracy, and companies with well-curated ground-truth teacher data can get huge value from small models tuned per use case.
Related event: Developer Distills DeepSeek V4 Flash into 4B Model on DGX Spark in 26 Hours(2 posts)→
More from Venture
- Mistral's valuation soared from $2.2B to $24B in under three years, and one observer now calls it underpriced — smlpth · 2026-11-04
- Gary Marcus: AI data center demand has already passed its peak as projects get killed — GaryMarcus · 2026-11-04
- AI stocks slide as Texas governor result raises data center risks — 1659447091 · 2026-11-04
- Gary Marcus: 'fleecing the public with AI fantasies just got harder' as AI stocks drop — GaryMarcus · 2026-11-04
- Dev's AI agents auto-submit his product to directories, 4 confirmed in 16hrs — pramodk73 · 2026-11-04
- Reddit case study: agent discovery optimization brought $14k MRR in a month — tomarv99 · 2026-11-04