GGUF, Q4, Q8, fp16: A Pleb’s Guide to LLM Quantization
Quantization is lossy compression for LLMs — same idea as JPEG for photos. It's the reason a used 3090 runs 70B models…
// d-central.tech / ai
Sovereign AI for Plebs
Self-hosted AI on hardware you already own. Credits all the open-source projects that made this possible. One more layer decentralized — the same sovereignty move Bitcoin made for money.
D-Central is shipping AI content and, soon, AI hardware and firmware built for the individual Bitcoiner who already thinks like a miner. DCENT_Inference OS and DCENT Heatbox AI are in closed beta under GPL-3.0, with public beta landing summer 2026. None of this replaces the Bitcoin core of the shop — the AI vertical is additive. Same hashcenter mindset, new compute workload.
Five entry points
Every post on this site slots into one of these five. Pick the one that matches where your head is at.
Sovereignty
Why self-hosted AI is the next cypherpunk battle.
Self-Hosting
The pleb's whole-stack guide to running AI locally.
Hardware
Which GPU runs which model. Buyer guides for the plebs.
Hashcenter
Hashcenter, not datacenter. Heat, sats, and sovereign intelligence under one roof.
Bitcoin × AI
When public miners left Bitcoin Hashcenters. Why plebs didn't.
Start here — the five-step path
Read these in order. By the end you’ll have a local model running on your box, a real UI in front of it, and enough theory to pick the right quant.
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1.
The narrative anchor. Why sovereign AI is the same move Bitcoin made for money.
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2.
Whole-stack overview — models, runners, hardware, the works.
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3.
Ten minutes from zero to a local model answering prompts on your own box.
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4.
A ChatGPT-shaped front end that talks to your Ollama node. No cloud.
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5.
GGUF, Q4, Q8, FP16 — what actually fits in your VRAM and why.
Fresh from the vertical
Newest posts across all six AI categories.
LM Studio vs Ollama vs llama.cpp: Which Runner for Plebs?
Three excellent open-source runners. Three different plebs. llama.cpp is the foundation Gerganov built. Ollama wraps it for daemon simplicity. LM Studio wraps…
Open WebUI: The ChatGPT Experience, But Yours
The terminal is fine for testing, unusable for daily driving. Open WebUI is the ChatGPT-style interface that plugs into your local Ollama…
BTC-AI Public Companies: The Hashcenter-to-Tokens Pivot
Hut 8, Core Scientific, IREN, and TeraWulf are leaving Bitcoin Hashcenters to become AI datacenter operators. It's a rational pivot for public…
Used RTX 3090 for LLMs in 2026: Still King?
24 GB of VRAM at $600–$800 used. For LLMs under 70B parameters at Q4–Q5 quants, the RTX 3090 is still the pleb…
From S19 to Your First AI Hashcenter
The mining shed is the hardest part of an AI Hashcenter — and you already have it. 240V service, airflow, sound isolation,…
Install Ollama and Run Your First Local LLM in 10 Minutes
Ten minutes, three commands, one evening. By the end you'll have Llama 3.1 or Gemma 3 running locally on your own hardware.…
Heating Your Home With Inference, Not Just Hashing
Bitcoin ASICs dump nearly all their power as heat — which is why mining heaters are a category. GPUs doing LLM inference…
Open-weight models, catalogued
Long-form model pages — architecture, quantizations, hardware that runs them. Built on the dc_ai_model CPT.
Mistral AI
Mistral AI's January 2025 24B model — Apache 2.0, competitive with Llama 3.3 70B, fits on a single…
Cohere
Cohere's April 2024 RAG-native flagship — 104B dense, first-class grounded citation and tool use, CC-BY-NC 4.0.
OpenAI
OpenAI's November 2023 open ASR model — 1.55B params, MIT-licensed, the open reference for multilingual speech-to-text.
Black Forest Labs
Black Forest Labs' August 2024 Apache 2.0 FLUX variant — 12B distilled to 1-4 steps for fast, commercially-open…
Stability AI
Stability AI's October 2024 MMDiT flagship — 2B (Medium) and 8B (Large) variants with dramatically improved prompt adherence…
Alibaba
Alibaba's May 2025 release — first open family with hybrid reasoning (toggle-able chain of thought), Apache 2.0 across…
GPUs, rigs, and the hashcenter retrofit
A dedicated hardware CPT plus benchmarks database ships in v1. Until then, the foundational reads:
- Used RTX 3090 for LLMs (2026 buyer’s guide) — the pleb’s go-to inference card.
- From S19 to AI hashcenter — retrofitting an ASIC room for inference.
Heads up: a full hardware CPT plus benchmarks taxonomy lands in a later task on the roadmap.
[closed beta] DCENT_Inference OS and DCENT Heatbox AI are in closed beta; public beta summer 2026. GPL-3.0. One more layer decentralized.