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FitStack starts from the job, not from a logo wall. You say what you are trying to do, what machine you have, and whether the data may leave the building. You get two or three alternatives: the easy cloud path, a builder-in-the-middle, and a local stack when the hardware can carry it.

We do not keep our own install tutorials. The steps live with the people who maintain them — MiaAI-Lab’s Spark recipes, NVIDIA’s playbooks and NemoClaw, OpenClaw, and xAI’s Grok Build surfaces. A field note here is a reason to click, plus an official one-liner when the authors published one.

Cloud rates come from OpenRouter, stamped with the date they were fetched. Street prices, local fits, and electricity are authored ballparks, not live listings. Beginner scores are our own judgement.

Recipes belong to their authors. FitStack does not maintain the install scripts.

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Ministral 3B

local · Updated 56 min ago

Price history is 3 days, from 2026-10-01. No week-ago price yet.

Scores

No score stored.

Skill.: No number
Coding.: No number
Tools.: No number
Context.: No number

History is 4 days, from 2026-09-27. No week-ago rank yet.

Cost

No hosted list cost for this model.

On your machine

Ministral 3B at Q4_K_M needs about 2 GB for the weights.

How to use it

No hosted model id is stored, so there is no API call to copy.

Template only. No GGUF file has been checked for Ministral 3B at Q4_K_M, so there is no llama-cli line to copy. About 2 GB for the weights.

llama.cpp

Search Hugging Face for a GGUF

No Ollama tag is stored for Ministral 3B, so there is no ollama run line to copy.

Ollama

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